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--- |
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language: |
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- en |
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- es |
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- ca |
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licence: apache-2.0 |
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tags: |
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- spanish |
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- catalan |
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- falcon-7b |
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datasets: |
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- BSC-LT/open_data_26B_tokens_balanced_es_ca |
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metrics: |
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- ppl |
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model-index: |
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- name: falcon_7b_balanced_tokenizer_fp16_CPT_open_data_26B_tokens_balanced_es_ca |
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results: |
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- task: |
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name: Causal Language Modeling |
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type: text-generation |
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dataset: |
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name: BSC-LT/open_data_26B_tokens_balanced_es_ca |
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type: Causal Language Modeling |
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config: default |
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split: validation |
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args: default |
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metrics: |
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- name: Perplexity |
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type: ppl |
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value: 8.59 |
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widget: |
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- text: |- |
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Respòn a la pregunta següent. |
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Pregunta: "Qui viu a França?" |
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Resposta: "A França viuen els francesos." |
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---- |
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Respòn a la pregunta següent. |
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Pregunta: "Quina és la capital de Suècia?" |
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Resposta: "La capital de Suècia és Estocolm." |
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---- |
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Respòn a la pregunta següent. |
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Pregunta: "Quina beguda es consumeix als matins per despertar-se?" |
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Resposta: "La majoria de gent consumeix cafè per despertar-se." |
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---- |
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Respòn a la pregunta següent. |
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Pregunta: "Qui és Leo Messi?" |
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Resposta: |
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example_title: Pregunta-Resposta |
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- text: |- |
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Extrae las entidades nombradas del siguiente texto: |
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Texto: "Me llamo Wolfgang y vivo en Berlin" |
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Entidades: Wolfgang:PER, Berlin:LOC |
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---- |
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Extrae las entidades nombradas del siguiente texto: |
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Texto: "Hoy voy a visitar el parc güell tras salir del barcelona supercomputing center" |
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Entidades: parc güell:LOC, barcelona supercomputing center:LOC |
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---- |
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Extrae las entidades nombradas del siguiente texto: |
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Texto: "Maria y Miguel no tienen ningún problema contigo" |
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Entidades: Maria:PER, Miguel:PER |
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---- |
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Extrae las entidades nombradas del siguiente texto: |
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Texto: "Damián se cortó el pelo" |
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Entidades: Damián:PER |
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---- |
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Extrae las entidades nombradas del siguiente texto: |
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Texto: "Lo mejor de Barcelona és el bar de mi amigo Pablo" |
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Entidades: Pablo:PER, Barcelona:LOC |
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---- |
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Extrae las entidades nombradas del siguiente texto: |
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Texto: "Carlos comparte piso con Marc" |
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Entidades: |
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example_title: Entidades-Nombradas |
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license: apache-2.0 |
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pipeline_tag: text-generation |
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--- |
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# falcon_7b_balanced_tokenizer_fp16_CPT_open_data_26B_tokens_balanced_es_ca |
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## Overview |
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This model is a new result towards the long-run problem of "What is the best strategy for training a model in my language (not English)?" |
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This model adapts the [falcon-7b](https://huggingface.co/tiiuae/falcon-7b) to the new target languages Spanish and Catalan by swapping the tokenizer and adjusting the embedding layer before training with 26B tokens in the target languages. |
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## Language Adaptation |
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When adapting a model from English to other languages the tokenizer plays a crucial role. |
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If the tokenizer does not include the target language in its training data, the resulting model will need many more tokens to perform the same task. |
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We solve this problem by creating a new tokenizer in the target languages (Spanish and Catalan) and adapting the embedding layer to it. |
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### New Tokenizer |
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We trained a new BPE Tokenizer for the Catalan and Spanish languages (equal representation). We shuffle a small amount of English in the mixture (since English is in the model training data). |
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The resulting data has the following language distribution: |
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|Language|%| |
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|---|---| |
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|En|16.84%| |
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|Es|41.38%| |
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|Ca|41.79%| |
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*P.D: It was meant to be the same distribution as the model train data (presented in Continual Pre-Training section)* |
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This reduces drastically the amount of tokens required to tokenize a text in the target languages (~70 %) while the English tokenization shows a small increase (~115 %). |
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### Embedding Layer Initialization |
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In order to fully take advantage of the English Pre-Training of the original Falcon model, we decided to re-use the embedding weights of the original model for those tokens shared between the two Tokenizers (the new and the old one). The rest of the embedding weights are initialized as the mean value of the weights of the original Tokenizer. |
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### Continual Pre-Training |
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Once the model has been successfully initialized, we continue its pre-training in the two target languages: Catalan and Spanish. We also shuffle a small amount of English in order to avoid catastrophic forgetting. The datasets used to train this model follow: |
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| Dataset | Language | Tokens (pre-epoch) | Epochs | |
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|---------------------|----------|--------------------|--------------| |
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| Wikipedia | en | 2169.97M | 1.428144485 | |
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| Lyrics | en | 100.60M | 0.7140722425 | |
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| C4_es | es | 53709.80M | 0.1049686196 | |
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| Biomedical | es | 455.03M | 0.7140722425 | |
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| Legal | es | 995.70M | 0.7140722425 | |
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| Wikipedia | es | 693.60M | 1.428144485 | |
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| Lyrics | es | 125.93M | 0.7140722425 | |
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| Gutenberg | es | 53.18M | 0.7140722425 | |
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| C4_ca | ca | 2826.00M | 2.142216727 | |
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| Biomedical | ca | 11.80M | 1.428144485 | |
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| RacoCatalá Noticias | ca | 17.16M | 2.142216727 | |
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| RacoCatalá Forums | ca | 333.73M | 2.142216727 | |
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| CaWaC | ca | 57.79M | 2.142216727 | |
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| Wikipedia | ca | 228.01M | 3.570361212 | |
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| Vilaweb | ca | 50.34M | 2.142216727 | |
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| Lyrics | ca | 0.50M | 2.142216727 | |
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The resulting dataset has the following language distribution: |
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|Language|%| |
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|---|---| |
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|En|16.84%| |
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|Es|41.38%| |
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|Ca|41.79%| |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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The model is ready-to-use only for causal language modeling to perform text-generation tasks. |
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However, it is intended to be fine-tuned on a generative downstream task. |
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## Limitations and biases |
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At the time of submission, no measures have been taken to estimate the bias and toxicity embedded in the model. |
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However, we are well aware that our models may be biased since the corpora have been collected using crawling techniques on multiple web sources. |
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We intend to conduct research in these areas in the future, and if completed, this model card will be updated. |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 1 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 8 |
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- total_train_batch_size: 8 |
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- total_eval_batch_size: 8 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 1.0 |
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### Training results |
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| Training Loss | Epoch | Step | Accuracy | Validation Loss | |
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|:-------------:|:-----:|:-------:|:--------:|:---------------:| |
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| 5.3279 | 0.0 | 5000 | 0.3133 | 3.9941 | |
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| 3.5754 | 0.0 | 10000 | 0.3824 | 3.3105 | |
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| 3.6102 | 0.0 | 15000 | 0.3977 | 3.1660 | |
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| 3.0639 | 0.01 | 20000 | 0.4134 | 3.0215 | |
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| 2.9477 | 0.01 | 25000 | 0.4252 | 2.9199 | |
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| 2.8589 | 0.01 | 30000 | 0.4315 | 2.8672 | |
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| 2.8063 | 0.01 | 35000 | 0.4388 | 2.8027 | |
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| 2.7646 | 0.01 | 40000 | 0.4419 | 2.7715 | |
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| 2.7306 | 0.01 | 45000 | 0.4467 | 2.7363 | |
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| 2.7106 | 0.01 | 50000 | 0.4493 | 2.7129 | |
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| 2.6829 | 0.02 | 55000 | 0.4522 | 2.6895 | |
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| 2.6703 | 0.02 | 60000 | 0.4537 | 2.6758 | |
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| 2.6522 | 0.02 | 65000 | 0.4560 | 2.6602 | |
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| 2.6377 | 0.02 | 70000 | 0.4574 | 2.6484 | |
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| 2.6241 | 0.02 | 75000 | 0.4587 | 2.6348 | |
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| 2.6159 | 0.02 | 80000 | 0.4604 | 2.625 | |
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| 2.5959 | 0.03 | 85000 | 0.4613 | 2.6133 | |
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| 2.5877 | 0.03 | 90000 | 0.4624 | 2.6035 | |
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| 2.5832 | 0.03 | 95000 | 0.4632 | 2.5996 | |
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| 2.5726 | 0.03 | 100000 | 0.4648 | 2.5859 | |
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| 2.5723 | 0.03 | 105000 | 0.4655 | 2.5801 | |
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| 2.5584 | 0.03 | 110000 | 0.4641 | 2.5938 | |
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| 2.5541 | 0.03 | 115000 | 0.4673 | 2.5664 | |
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| 2.541 | 0.04 | 120000 | 0.4684 | 2.5586 | |
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| 2.5359 | 0.04 | 125000 | 0.4674 | 2.5645 | |
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| 2.5298 | 0.04 | 130000 | 0.4699 | 2.5449 | |
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| 2.5258 | 0.04 | 135000 | 0.4703 | 2.5410 | |
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| 2.5207 | 0.04 | 140000 | 0.4709 | 2.5371 | |
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| 2.5167 | 0.04 | 145000 | 0.4719 | 2.5312 | |
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| 2.5101 | 0.04 | 150000 | 0.4702 | 2.5449 | |
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| 2.5058 | 0.05 | 155000 | 0.4730 | 2.5215 | |
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| 2.5021 | 0.05 | 160000 | 0.4734 | 2.5195 | |
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| 2.8135 | 0.05 | 165000 | 0.4317 | 2.8320 | |
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| 2.7932 | 0.05 | 170000 | 0.4730 | 2.5215 | |
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| 2.4914 | 0.05 | 175000 | 0.4752 | 2.5059 | |
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| 2.487 | 0.05 | 180000 | 0.4754 | 2.5039 | |
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| 2.4829 | 0.06 | 185000 | 0.4751 | 2.5039 | |
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| 2.4778 | 0.06 | 190000 | 0.4763 | 2.4961 | |
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| 2.4779 | 0.06 | 195000 | 0.4770 | 2.4922 | |
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| 2.4685 | 0.06 | 200000 | 0.4766 | 2.4941 | |
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| 2.4661 | 0.06 | 205000 | 0.4776 | 2.4844 | |
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| 2.4579 | 0.06 | 210000 | 0.4783 | 2.4805 | |
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| 2.4589 | 0.06 | 215000 | 0.4788 | 2.4785 | |
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| 2.4571 | 0.07 | 220000 | 0.4793 | 2.4746 | |
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| 2.4504 | 0.07 | 225000 | 0.4797 | 2.4727 | |
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| 2.4538 | 0.07 | 230000 | 0.4800 | 2.4688 | |
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| 2.4481 | 0.07 | 235000 | 0.4806 | 2.4668 | |
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| 2.4454 | 0.07 | 240000 | 0.4810 | 2.4609 | |
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| 2.44 | 0.07 | 245000 | 0.4811 | 2.4590 | |
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| 2.4392 | 0.07 | 250000 | 0.4811 | 2.4590 | |
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| 2.431 | 0.08 | 255000 | 0.4813 | 2.4570 | |
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| 2.4377 | 0.08 | 260000 | 0.4823 | 2.4512 | |
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| 2.4299 | 0.08 | 265000 | 0.4826 | 2.4473 | |
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| 2.4283 | 0.08 | 270000 | 0.4828 | 2.4473 | |
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| 2.4256 | 0.08 | 275000 | 0.4833 | 2.4434 | |
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| 2.4198 | 0.08 | 280000 | 0.4838 | 2.4414 | |
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| 2.4174 | 0.09 | 285000 | 0.4840 | 2.4414 | |
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| 2.4151 | 0.09 | 290000 | 0.4844 | 2.4355 | |
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| 2.4191 | 0.09 | 295000 | 0.4847 | 2.4336 | |
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| 2.4071 | 0.09 | 300000 | 0.4848 | 2.4316 | |
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| 2.4126 | 0.09 | 305000 | 0.4855 | 2.4277 | |
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| 2.4053 | 0.09 | 310000 | 0.4851 | 2.4297 | |
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| 2.4071 | 0.09 | 315000 | 0.4858 | 2.4258 | |
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| 2.4027 | 0.1 | 320000 | 0.4866 | 2.4219 | |
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| 2.4013 | 0.1 | 325000 | 0.4867 | 2.4180 | |
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| 2.4032 | 0.1 | 330000 | 0.4866 | 2.4180 | |
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| 2.3919 | 0.1 | 335000 | 0.4871 | 2.4160 | |
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| 2.3936 | 0.1 | 340000 | 0.4873 | 2.4141 | |
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| 2.3905 | 0.1 | 345000 | 0.4878 | 2.4102 | |
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| 2.3889 | 0.1 | 350000 | 0.4881 | 2.4102 | |
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| 2.3866 | 0.11 | 355000 | 0.4884 | 2.4082 | |
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| 2.3823 | 0.11 | 360000 | 0.4888 | 2.4062 | |
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| 2.3828 | 0.11 | 365000 | 0.4888 | 2.4023 | |
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| 2.3795 | 0.11 | 370000 | 0.4889 | 2.4004 | |
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| 2.3812 | 0.11 | 375000 | 0.4868 | 2.4160 | |
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| 2.3789 | 0.11 | 380000 | 0.4896 | 2.3965 | |
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| 2.372 | 0.12 | 385000 | 0.4895 | 2.3965 | |
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| 2.3732 | 0.12 | 390000 | 0.4899 | 2.3965 | |
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| 2.3725 | 0.12 | 395000 | 0.4903 | 2.3926 | |
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| 2.3716 | 0.12 | 400000 | 0.4904 | 2.3906 | |
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| 2.3709 | 0.12 | 405000 | 0.4904 | 2.3906 | |
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| 2.3619 | 0.12 | 410000 | 0.4906 | 2.3887 | |
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| 2.367 | 0.12 | 415000 | 0.4912 | 2.3867 | |
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| 2.3639 | 0.13 | 420000 | 0.4912 | 2.3848 | |
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| 2.3621 | 0.13 | 425000 | 0.4919 | 2.3828 | |
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| 2.3578 | 0.13 | 430000 | 0.4920 | 2.3809 | |
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| 2.3608 | 0.13 | 435000 | 0.4922 | 2.3789 | |
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| 2.3541 | 0.13 | 440000 | 0.4923 | 2.3770 | |
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| 2.3556 | 0.13 | 445000 | 0.4926 | 2.3770 | |
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| 2.3562 | 0.13 | 450000 | 0.4928 | 2.3770 | |
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| 2.3641 | 0.14 | 455000 | 0.4910 | 2.3867 | |
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| 2.3641 | 0.14 | 460000 | 0.4911 | 2.3867 | |
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| 2.3646 | 0.14 | 465000 | 0.4911 | 2.3867 | |
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| 2.3629 | 0.14 | 470000 | 0.4911 | 2.3848 | |
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| 2.3659 | 0.14 | 475000 | 0.4914 | 2.3828 | |
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| 2.3651 | 0.14 | 480000 | 0.4916 | 2.3828 | |
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| 2.3608 | 0.15 | 485000 | 0.4918 | 2.3809 | |
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| 2.3612 | 0.15 | 490000 | 0.4920 | 2.3809 | |
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| 2.3569 | 0.15 | 495000 | 0.4922 | 2.3789 | |
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| 2.3557 | 0.15 | 500000 | 0.4923 | 2.3789 | |
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| 2.3541 | 0.15 | 505000 | 0.4922 | 2.3770 | |
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| 2.351 | 0.15 | 510000 | 0.4927 | 2.375 | |
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| 2.3504 | 0.15 | 515000 | 0.4926 | 2.375 | |
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| 2.3479 | 0.16 | 520000 | 0.4929 | 2.3730 | |
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| 2.3451 | 0.16 | 525000 | 0.4929 | 2.3711 | |
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| 2.3505 | 0.16 | 530000 | 0.4934 | 2.3691 | |
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| 2.3457 | 0.16 | 535000 | 0.4934 | 2.3691 | |
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| 2.3479 | 0.16 | 540000 | 0.4937 | 2.3691 | |
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| 2.3421 | 0.16 | 545000 | 0.4936 | 2.3672 | |
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| 2.3433 | 0.16 | 550000 | 0.4937 | 2.3672 | |
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| 2.3425 | 0.17 | 555000 | 0.4939 | 2.3652 | |
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| 2.3403 | 0.17 | 560000 | 0.4942 | 2.3633 | |
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| 2.3417 | 0.17 | 565000 | 0.4944 | 2.3613 | |
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| 2.3382 | 0.17 | 570000 | 0.4947 | 2.3613 | |
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| 2.3354 | 0.17 | 575000 | 0.4949 | 2.3594 | |
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| 2.3366 | 0.17 | 580000 | 0.4947 | 2.3594 | |
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| 2.3373 | 0.18 | 585000 | 0.4945 | 2.3594 | |
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| 2.3365 | 0.18 | 590000 | 0.4949 | 2.3594 | |
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| 2.3318 | 0.18 | 595000 | 0.4953 | 2.3555 | |
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| 2.3278 | 0.18 | 600000 | 0.4958 | 2.3535 | |
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| 2.3277 | 0.18 | 605000 | 0.4959 | 2.3516 | |
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| 2.326 | 0.18 | 610000 | 0.4961 | 2.3516 | |
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| 2.3273 | 0.18 | 615000 | 0.4961 | 2.3516 | |
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| 2.3284 | 0.19 | 620000 | 0.4965 | 2.3496 | |
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| 2.3276 | 0.19 | 625000 | 0.4966 | 2.3477 | |
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| 2.3228 | 0.19 | 630000 | 0.4967 | 2.3457 | |
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| 2.3219 | 0.19 | 635000 | 0.4968 | 2.3457 | |
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| 2.326 | 0.19 | 640000 | 0.4970 | 2.3438 | |
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| 2.3191 | 0.19 | 645000 | 0.4972 | 2.3418 | |
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| 2.3167 | 0.19 | 650000 | 0.4973 | 2.3438 | |
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| 2.3172 | 0.2 | 655000 | 0.4974 | 2.3418 | |
|
| 2.3194 | 0.2 | 660000 | 0.4977 | 2.3379 | |
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| 2.3204 | 0.2 | 665000 | 0.4976 | 2.3398 | |
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| 2.309 | 0.2 | 670000 | 0.4980 | 2.3359 | |
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| 2.3147 | 0.2 | 675000 | 0.4981 | 2.3379 | |
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| 2.3122 | 0.2 | 680000 | 0.4980 | 2.3359 | |
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| 2.3096 | 0.21 | 685000 | 0.4984 | 2.3340 | |
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| 2.3093 | 0.21 | 690000 | 0.4986 | 2.3340 | |
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| 2.3048 | 0.21 | 695000 | 0.4985 | 2.3320 | |
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| 2.3111 | 0.21 | 700000 | 0.4988 | 2.3301 | |
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| 2.3074 | 0.21 | 705000 | 0.4989 | 2.3301 | |
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| 2.3082 | 0.21 | 710000 | 0.4992 | 2.3301 | |
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| 2.3093 | 0.21 | 715000 | 0.4994 | 2.3281 | |
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| 2.3011 | 0.22 | 720000 | 0.4995 | 2.3281 | |
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| 2.2998 | 0.22 | 725000 | 0.4995 | 2.3262 | |
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| 2.3012 | 0.22 | 730000 | 0.4996 | 2.3262 | |
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| 2.3002 | 0.22 | 735000 | 0.4997 | 2.3242 | |
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| 2.2994 | 0.22 | 740000 | 0.5000 | 2.3242 | |
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| 2.299 | 0.22 | 745000 | 0.5001 | 2.3223 | |
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| 2.2969 | 0.22 | 750000 | 0.5003 | 2.3223 | |
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| 2.2934 | 0.23 | 755000 | 0.5004 | 2.3203 | |
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| 2.2988 | 0.23 | 760000 | 0.5005 | 2.3184 | |
|
| 2.2911 | 0.23 | 765000 | 0.5007 | 2.3184 | |
|
| 2.2929 | 0.23 | 770000 | 0.5008 | 2.3184 | |
|
| 2.2926 | 0.23 | 775000 | 0.5009 | 2.3164 | |
|
| 2.292 | 0.23 | 780000 | 0.5012 | 2.3164 | |
|
| 2.2932 | 0.24 | 785000 | 0.5014 | 2.3145 | |
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| 2.2903 | 0.24 | 790000 | 0.5014 | 2.3145 | |
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| 2.2886 | 0.24 | 795000 | 0.5015 | 2.3125 | |
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| 2.2924 | 0.24 | 800000 | 0.5015 | 2.3125 | |
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| 2.2891 | 0.24 | 805000 | 0.5019 | 2.3105 | |
|
| 2.2862 | 0.24 | 810000 | 0.5020 | 2.3086 | |
|
| 2.2858 | 0.24 | 815000 | 0.5022 | 2.3086 | |
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| 2.2841 | 0.25 | 820000 | 0.5023 | 2.3066 | |
|
| 2.2843 | 0.25 | 825000 | 0.5022 | 2.3086 | |
|
| 2.2832 | 0.25 | 830000 | 0.5025 | 2.3066 | |
|
| 2.2846 | 0.25 | 835000 | 0.5026 | 2.3066 | |
|
| 2.2784 | 0.25 | 840000 | 0.5027 | 2.3047 | |
|
| 2.277 | 0.25 | 845000 | 0.5028 | 2.3027 | |
|
| 2.276 | 0.25 | 850000 | 0.5026 | 2.3066 | |
|
| 2.2802 | 0.26 | 855000 | 0.5031 | 2.3027 | |
|
| 2.2781 | 0.26 | 860000 | 0.5032 | 2.3008 | |
|
| 2.2749 | 0.26 | 865000 | 0.5038 | 2.2988 | |
|
| 2.2729 | 0.26 | 870000 | 0.5037 | 2.2969 | |
|
| 2.2708 | 0.26 | 875000 | 0.5039 | 2.2969 | |
|
| 2.2754 | 0.26 | 880000 | 0.5039 | 2.2969 | |
|
| 2.2761 | 0.27 | 885000 | 0.5041 | 2.2949 | |
|
| 2.2742 | 0.27 | 890000 | 0.5041 | 2.2949 | |
|
| 2.2734 | 0.27 | 895000 | 0.5041 | 2.2949 | |
|
| 2.2682 | 0.27 | 900000 | 0.5044 | 2.2930 | |
|
| 2.2667 | 0.27 | 905000 | 0.5045 | 2.2930 | |
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| 2.2676 | 0.27 | 910000 | 0.5046 | 2.2930 | |
|
| 2.2707 | 0.27 | 915000 | 0.5047 | 2.2910 | |
|
| 2.265 | 0.28 | 920000 | 0.5048 | 2.2910 | |
|
| 2.2676 | 0.28 | 925000 | 0.5046 | 2.2910 | |
|
| 2.2662 | 0.28 | 930000 | 0.5052 | 2.2891 | |
|
| 2.2706 | 0.28 | 935000 | 0.5051 | 2.2891 | |
|
| 2.2657 | 0.28 | 940000 | 0.5049 | 2.2891 | |
|
| 2.2672 | 0.28 | 945000 | 0.5050 | 2.2871 | |
|
| 2.2716 | 0.28 | 950000 | 0.5037 | 2.2969 | |
|
| 2.2702 | 0.29 | 955000 | 0.5037 | 2.2988 | |
|
| 2.2708 | 0.29 | 960000 | 0.5035 | 2.2988 | |
|
| 2.2738 | 0.29 | 965000 | 0.5035 | 2.2988 | |
|
| 2.2737 | 0.29 | 970000 | 0.5036 | 2.2988 | |
|
| 2.2763 | 0.29 | 975000 | 0.4987 | 2.3301 | |
|
| 2.2738 | 0.29 | 980000 | 0.5035 | 2.2969 | |
|
| 2.2737 | 0.3 | 985000 | 0.5036 | 2.2969 | |
|
| 2.2748 | 0.3 | 990000 | 0.5036 | 2.2969 | |
|
| 2.2724 | 0.3 | 995000 | 0.5038 | 2.2969 | |
|
| 2.2744 | 0.3 | 1000000 | 0.5033 | 2.2988 | |
|
| 2.2694 | 0.3 | 1005000 | 0.5033 | 2.2988 | |
|
| 2.2684 | 0.3 | 1010000 | 0.5039 | 2.2949 | |
|
| 2.2731 | 0.3 | 1015000 | 0.5040 | 2.2949 | |
|
| 2.2714 | 0.31 | 1020000 | 0.5042 | 2.2949 | |
|
| 2.2687 | 0.31 | 1025000 | 0.5045 | 2.2930 | |
|
| 2.2673 | 0.31 | 1030000 | 0.5046 | 2.2930 | |
|
| 2.2677 | 0.31 | 1035000 | 0.5044 | 2.2930 | |
|
| 2.265 | 0.31 | 1040000 | 0.5047 | 2.2910 | |
|
| 2.2659 | 0.31 | 1045000 | 0.5045 | 2.2910 | |
|
| 2.2633 | 0.31 | 1050000 | 0.5042 | 2.2949 | |
|
| 2.2689 | 0.32 | 1055000 | 0.5050 | 2.2891 | |
|
| 2.2617 | 0.32 | 1060000 | 0.5049 | 2.2891 | |
|
| 2.2613 | 0.32 | 1065000 | 0.5052 | 2.2871 | |
|
| 2.2649 | 0.32 | 1070000 | 0.5047 | 2.2891 | |
|
| 2.2587 | 0.32 | 1075000 | 0.5053 | 2.2871 | |
|
| 2.2641 | 0.32 | 1080000 | 0.5054 | 2.2852 | |
|
| 2.2634 | 0.33 | 1085000 | 0.5057 | 2.2852 | |
|
| 2.2597 | 0.33 | 1090000 | 0.5057 | 2.2832 | |
|
| 2.2572 | 0.33 | 1095000 | 0.5060 | 2.2832 | |
|
| 2.2566 | 0.33 | 1100000 | 0.5056 | 2.2832 | |
|
| 2.2576 | 0.33 | 1105000 | 0.5056 | 2.2832 | |
|
| 2.2612 | 0.33 | 1110000 | 0.5057 | 2.2832 | |
|
| 2.2585 | 0.33 | 1115000 | 0.5059 | 2.2812 | |
|
| 2.2528 | 0.34 | 1120000 | 0.5060 | 2.2812 | |
|
| 2.2599 | 0.34 | 1125000 | 0.5060 | 2.2812 | |
|
| 2.2556 | 0.34 | 1130000 | 0.5066 | 2.2773 | |
|
| 2.2519 | 0.34 | 1135000 | 0.5064 | 2.2793 | |
|
| 2.2567 | 0.34 | 1140000 | 0.5068 | 2.2773 | |
|
| 2.2516 | 0.34 | 1145000 | 0.5069 | 2.2754 | |
|
| 2.2533 | 0.34 | 1150000 | 0.5068 | 2.2754 | |
|
| 2.2532 | 0.35 | 1155000 | 0.5070 | 2.2754 | |
|
| 2.2572 | 0.35 | 1160000 | 0.5064 | 2.2793 | |
|
| 2.2514 | 0.35 | 1165000 | 0.5072 | 2.2734 | |
|
| 2.2471 | 0.35 | 1170000 | 0.5073 | 2.2734 | |
|
| 2.2524 | 0.35 | 1175000 | 0.5076 | 2.2715 | |
|
| 2.247 | 0.35 | 1180000 | 0.5073 | 2.2715 | |
|
| 2.2491 | 0.35 | 1185000 | 0.5077 | 2.2715 | |
|
| 2.2481 | 0.36 | 1190000 | 0.5078 | 2.2695 | |
|
| 2.2465 | 0.36 | 1195000 | 0.5069 | 2.2734 | |
|
| 2.2494 | 0.36 | 1200000 | 0.5067 | 2.2793 | |
|
| 2.2541 | 0.36 | 1205000 | 0.5069 | 2.2754 | |
|
| 2.25 | 0.36 | 1210000 | 0.5067 | 2.2754 | |
|
| 2.25 | 0.36 | 1215000 | 0.5064 | 2.2793 | |
|
| 2.2508 | 0.37 | 1220000 | 0.5070 | 2.2734 | |
|
| 2.2496 | 0.37 | 1225000 | 0.5070 | 2.2734 | |
|
| 2.2499 | 0.37 | 1230000 | 0.5073 | 2.2734 | |
|
| 2.2467 | 0.37 | 1235000 | 0.5076 | 2.2715 | |
|
| 2.2497 | 0.37 | 1240000 | 0.5073 | 2.2715 | |
|
| 2.2463 | 0.37 | 1245000 | 0.5073 | 2.2715 | |
|
| 2.2479 | 0.37 | 1250000 | 0.5078 | 2.2695 | |
|
| 2.2445 | 0.38 | 1255000 | 0.5079 | 2.2695 | |
|
| 2.247 | 0.38 | 1260000 | 0.5078 | 2.2695 | |
|
| 2.2443 | 0.38 | 1265000 | 0.5079 | 2.2676 | |
|
| 2.243 | 0.38 | 1270000 | 0.5081 | 2.2676 | |
|
| 2.2454 | 0.38 | 1275000 | 0.5077 | 2.2715 | |
|
| 2.2451 | 0.38 | 1280000 | 0.5081 | 2.2695 | |
|
| 2.2455 | 0.38 | 1285000 | 0.5084 | 2.2656 | |
|
| 2.241 | 0.39 | 1290000 | 0.5083 | 2.2676 | |
|
| 2.243 | 0.39 | 1295000 | 0.5086 | 2.2637 | |
|
| 2.2408 | 0.39 | 1300000 | 0.5084 | 2.2637 | |
|
| 2.2508 | 0.39 | 1305000 | 0.5063 | 2.2793 | |
|
| 2.252 | 0.39 | 1310000 | 0.5047 | 2.2910 | |
|
| 2.7482 | 0.39 | 1315000 | 0.4506 | 2.6465 | |
|
| 2.4189 | 0.4 | 1320000 | 0.5070 | 2.2754 | |
|
| 2.2446 | 0.4 | 1325000 | 0.5081 | 2.2676 | |
|
| 2.2416 | 0.4 | 1330000 | 0.5087 | 2.2637 | |
|
| 2.2421 | 0.4 | 1335000 | 0.5088 | 2.2617 | |
|
| 2.2367 | 0.4 | 1340000 | 0.5092 | 2.2617 | |
|
| 2.2355 | 0.4 | 1345000 | 0.5091 | 2.2598 | |
|
| 2.2379 | 0.4 | 1350000 | 0.5094 | 2.2598 | |
|
| 2.2365 | 0.41 | 1355000 | 0.5094 | 2.2598 | |
|
| 2.2379 | 0.41 | 1360000 | 0.5091 | 2.2578 | |
|
| 2.235 | 0.41 | 1365000 | 0.5095 | 2.2578 | |
|
| 2.236 | 0.41 | 1370000 | 0.5093 | 2.2578 | |
|
| 2.2344 | 0.41 | 1375000 | 0.5095 | 2.2578 | |
|
| 2.2348 | 0.41 | 1380000 | 0.5096 | 2.2559 | |
|
| 2.2306 | 0.41 | 1385000 | 0.5097 | 2.2559 | |
|
| 2.2293 | 0.42 | 1390000 | 0.5098 | 2.2559 | |
|
| 2.2311 | 0.42 | 1395000 | 0.5101 | 2.2539 | |
|
| 2.231 | 0.42 | 1400000 | 0.5101 | 2.2539 | |
|
| 2.2272 | 0.42 | 1405000 | 0.5102 | 2.2520 | |
|
| 2.2264 | 0.42 | 1410000 | 0.5102 | 2.2539 | |
|
| 2.2295 | 0.42 | 1415000 | 0.5104 | 2.2520 | |
|
| 2.2281 | 0.43 | 1420000 | 0.5104 | 2.2520 | |
|
| 2.2234 | 0.43 | 1425000 | 0.5107 | 2.25 | |
|
| 2.2293 | 0.43 | 1430000 | 0.5107 | 2.25 | |
|
| 2.2256 | 0.43 | 1435000 | 0.5109 | 2.25 | |
|
| 2.2247 | 0.43 | 1440000 | 0.5108 | 2.25 | |
|
| 2.222 | 0.43 | 1445000 | 0.5108 | 2.25 | |
|
| 2.2228 | 0.43 | 1450000 | 0.5106 | 2.2480 | |
|
| 2.2241 | 0.44 | 1455000 | 0.5111 | 2.2480 | |
|
| 2.2219 | 0.44 | 1460000 | 0.5111 | 2.2461 | |
|
| 2.2219 | 0.44 | 1465000 | 0.5113 | 2.2461 | |
|
| 2.2215 | 0.44 | 1470000 | 0.5113 | 2.2461 | |
|
| 2.2193 | 0.44 | 1475000 | 0.5116 | 2.2441 | |
|
| 2.2183 | 0.44 | 1480000 | 0.5115 | 2.2441 | |
|
| 2.2177 | 0.44 | 1485000 | 0.5116 | 2.2441 | |
|
| 2.2211 | 0.45 | 1490000 | 0.5116 | 2.2422 | |
|
| 2.2183 | 0.45 | 1495000 | 0.5118 | 2.2422 | |
|
| 2.2182 | 0.45 | 1500000 | 0.5120 | 2.2402 | |
|
| 2.2148 | 0.45 | 1505000 | 0.5122 | 2.2402 | |
|
| 2.2217 | 0.45 | 1510000 | 0.5123 | 2.2402 | |
|
| 2.2117 | 0.45 | 1515000 | 0.5124 | 2.2383 | |
|
| 2.2152 | 0.46 | 1520000 | 0.5123 | 2.2383 | |
|
| 2.2148 | 0.46 | 1525000 | 0.5125 | 2.2383 | |
|
| 2.2151 | 0.46 | 1530000 | 0.5127 | 2.2363 | |
|
| 2.2129 | 0.46 | 1535000 | 0.5127 | 2.2363 | |
|
| 2.2145 | 0.46 | 1540000 | 0.5128 | 2.2363 | |
|
| 2.2099 | 0.46 | 1545000 | 0.5129 | 2.2363 | |
|
| 2.2125 | 0.46 | 1550000 | 0.5132 | 2.2344 | |
|
| 2.2101 | 0.47 | 1555000 | 0.5131 | 2.2344 | |
|
| 2.211 | 0.47 | 1560000 | 0.5132 | 2.2344 | |
|
| 2.2086 | 0.47 | 1565000 | 0.5132 | 2.2344 | |
|
| 2.2137 | 0.47 | 1570000 | 0.5132 | 2.2324 | |
|
| 2.2122 | 0.47 | 1575000 | 0.5134 | 2.2324 | |
|
| 2.2053 | 0.47 | 1580000 | 0.5134 | 2.2324 | |
|
| 2.208 | 0.47 | 1585000 | 0.5134 | 2.2305 | |
|
| 2.2081 | 0.48 | 1590000 | 0.5136 | 2.2305 | |
|
| 2.2077 | 0.48 | 1595000 | 0.5138 | 2.2305 | |
|
| 2.2061 | 0.48 | 1600000 | 0.5136 | 2.2305 | |
|
| 2.2055 | 0.48 | 1605000 | 0.5139 | 2.2285 | |
|
| 2.2065 | 0.48 | 1610000 | 0.5139 | 2.2285 | |
|
| 2.2054 | 0.48 | 1615000 | 0.5139 | 2.2285 | |
|
| 2.2035 | 0.49 | 1620000 | 0.5140 | 2.2285 | |
|
| 2.2021 | 0.49 | 1625000 | 0.5140 | 2.2285 | |
|
| 2.2036 | 0.49 | 1630000 | 0.5138 | 2.2285 | |
|
| 2.204 | 0.49 | 1635000 | 0.5140 | 2.2266 | |
|
| 2.2042 | 0.49 | 1640000 | 0.5141 | 2.2266 | |
|
| 2.2024 | 0.49 | 1645000 | 0.5142 | 2.2266 | |
|
| 2.2023 | 0.49 | 1650000 | 0.5144 | 2.2266 | |
|
| 2.1976 | 0.5 | 1655000 | 0.5146 | 2.2246 | |
|
| 2.2028 | 0.5 | 1660000 | 0.5147 | 2.2246 | |
|
| 2.1971 | 0.5 | 1665000 | 0.5146 | 2.2246 | |
|
| 2.1978 | 0.5 | 1670000 | 0.5146 | 2.2246 | |
|
| 2.1955 | 0.5 | 1675000 | 0.5148 | 2.2227 | |
|
| 2.1967 | 0.5 | 1680000 | 0.5147 | 2.2227 | |
|
| 2.1975 | 0.5 | 1685000 | 0.5152 | 2.2227 | |
|
| 2.1972 | 0.51 | 1690000 | 0.5149 | 2.2207 | |
|
| 2.1967 | 0.51 | 1695000 | 0.5151 | 2.2207 | |
|
| 2.194 | 0.51 | 1700000 | 0.5151 | 2.2207 | |
|
| 2.2009 | 0.51 | 1705000 | 0.5139 | 2.2285 | |
|
| 2.2085 | 0.51 | 1710000 | 0.5136 | 2.2305 | |
|
| 2.2077 | 0.51 | 1715000 | 0.5137 | 2.2305 | |
|
| 2.205 | 0.52 | 1720000 | 0.5134 | 2.2305 | |
|
| 2.2063 | 0.52 | 1725000 | 0.5134 | 2.2305 | |
|
| 2.2076 | 0.52 | 1730000 | 0.5135 | 2.2305 | |
|
| 2.2036 | 0.52 | 1735000 | 0.5133 | 2.2305 | |
|
| 2.2064 | 0.52 | 1740000 | 0.5138 | 2.2305 | |
|
| 2.2053 | 0.52 | 1745000 | 0.5137 | 2.2305 | |
|
| 2.2048 | 0.52 | 1750000 | 0.5139 | 2.2305 | |
|
| 2.2075 | 0.53 | 1755000 | 0.5138 | 2.2305 | |
|
| 2.2041 | 0.53 | 1760000 | 0.5136 | 2.2285 | |
|
| 2.2057 | 0.53 | 1765000 | 0.5139 | 2.2285 | |
|
| 2.2054 | 0.53 | 1770000 | 0.5139 | 2.2285 | |
|
| 2.2085 | 0.53 | 1775000 | 0.5139 | 2.2285 | |
|
| 2.2051 | 0.53 | 1780000 | 0.5141 | 2.2266 | |
|
| 2.2023 | 0.53 | 1785000 | 0.5139 | 2.2266 | |
|
| 2.205 | 0.54 | 1790000 | 0.5141 | 2.2266 | |
|
| 2.2009 | 0.54 | 1795000 | 0.5141 | 2.2266 | |
|
| 2.1998 | 0.54 | 1800000 | 0.5143 | 2.2266 | |
|
| 2.2009 | 0.54 | 1805000 | 0.5144 | 2.2246 | |
|
| 2.2027 | 0.54 | 1810000 | 0.5143 | 2.2266 | |
|
| 2.2007 | 0.54 | 1815000 | 0.5146 | 2.2246 | |
|
| 2.1978 | 0.55 | 1820000 | 0.5145 | 2.2246 | |
|
| 2.1999 | 0.55 | 1825000 | 0.5146 | 2.2227 | |
|
| 2.1978 | 0.55 | 1830000 | 0.5148 | 2.2227 | |
|
| 2.1989 | 0.55 | 1835000 | 0.5147 | 2.2227 | |
|
| 2.1989 | 0.55 | 1840000 | 0.5148 | 2.2227 | |
|
| 2.1982 | 0.55 | 1845000 | 0.5150 | 2.2207 | |
|
| 2.1974 | 0.55 | 1850000 | 0.5151 | 2.2207 | |
|
| 2.1972 | 0.56 | 1855000 | 0.5151 | 2.2207 | |
|
| 2.1966 | 0.56 | 1860000 | 0.5151 | 2.2207 | |
|
| 2.198 | 0.56 | 1865000 | 0.5150 | 2.2207 | |
|
| 2.1978 | 0.56 | 1870000 | 0.5152 | 2.2207 | |
|
| 2.1938 | 0.56 | 1875000 | 0.5152 | 2.2207 | |
|
| 2.1908 | 0.56 | 1880000 | 0.5152 | 2.2188 | |
|
| 2.1899 | 0.56 | 1885000 | 0.5152 | 2.2188 | |
|
| 2.1938 | 0.57 | 1890000 | 0.5152 | 2.2188 | |
|
| 2.1909 | 0.57 | 1895000 | 0.5154 | 2.2188 | |
|
| 2.1921 | 0.57 | 1900000 | 0.5155 | 2.2188 | |
|
| 2.1926 | 0.57 | 1905000 | 0.5156 | 2.2168 | |
|
| 2.194 | 0.57 | 1910000 | 0.5154 | 2.2168 | |
|
| 2.1942 | 0.57 | 1915000 | 0.5152 | 2.2188 | |
|
| 2.1947 | 0.58 | 1920000 | 0.5151 | 2.2188 | |
|
| 2.1941 | 0.58 | 1925000 | 0.5151 | 2.2207 | |
|
| 2.1984 | 0.58 | 1930000 | 0.5152 | 2.2207 | |
|
| 2.1929 | 0.58 | 1935000 | 0.5151 | 2.2207 | |
|
| 2.1921 | 0.58 | 1940000 | 0.5154 | 2.2188 | |
|
| 2.1932 | 0.58 | 1945000 | 0.5153 | 2.2188 | |
|
| 2.1959 | 0.58 | 1950000 | 0.5154 | 2.2188 | |
|
| 2.1927 | 0.59 | 1955000 | 0.5154 | 2.2188 | |
|
| 2.1949 | 0.59 | 1960000 | 0.5155 | 2.2188 | |
|
| 2.1918 | 0.59 | 1965000 | 0.5154 | 2.2168 | |
|
| 2.1957 | 0.59 | 1970000 | 0.5155 | 2.2168 | |
|
| 2.1884 | 0.59 | 1975000 | 0.5157 | 2.2168 | |
|
| 2.1942 | 0.59 | 1980000 | 0.5156 | 2.2148 | |
|
| 2.1938 | 0.59 | 1985000 | 0.5156 | 2.2168 | |
|
| 2.1935 | 0.6 | 1990000 | 0.5160 | 2.2148 | |
|
| 2.1902 | 0.6 | 1995000 | 0.5157 | 2.2148 | |
|
| 2.188 | 0.6 | 2000000 | 0.5158 | 2.2148 | |
|
| 2.1862 | 0.6 | 2005000 | 0.5159 | 2.2129 | |
|
| 2.1886 | 0.6 | 2010000 | 0.5161 | 2.2129 | |
|
| 2.1811 | 0.6 | 2015000 | 0.5161 | 2.2129 | |
|
| 2.19 | 0.61 | 2020000 | 0.5160 | 2.2129 | |
|
| 2.1895 | 0.61 | 2025000 | 0.5165 | 2.2129 | |
|
| 2.1904 | 0.61 | 2030000 | 0.5161 | 2.2129 | |
|
| 2.1854 | 0.61 | 2035000 | 0.5165 | 2.2129 | |
|
| 2.1883 | 0.61 | 2040000 | 0.5165 | 2.2109 | |
|
| 2.1859 | 0.61 | 2045000 | 0.5165 | 2.2109 | |
|
| 2.1849 | 0.61 | 2050000 | 0.5168 | 2.2090 | |
|
| 2.1844 | 0.62 | 2055000 | 0.5167 | 2.2109 | |
|
| 2.1866 | 0.62 | 2060000 | 0.5167 | 2.2090 | |
|
| 2.1865 | 0.62 | 2065000 | 0.5168 | 2.2090 | |
|
| 2.1846 | 0.62 | 2070000 | 0.5171 | 2.2070 | |
|
| 2.1821 | 0.62 | 2075000 | 0.5170 | 2.2070 | |
|
| 2.184 | 0.62 | 2080000 | 0.5170 | 2.2070 | |
|
| 2.1847 | 0.62 | 2085000 | 0.5173 | 2.2051 | |
|
| 2.1836 | 0.63 | 2090000 | 0.5174 | 2.2051 | |
|
| 2.1791 | 0.63 | 2095000 | 0.5174 | 2.2051 | |
|
| 2.1812 | 0.63 | 2100000 | 0.5173 | 2.2051 | |
|
| 2.1835 | 0.63 | 2105000 | 0.5176 | 2.2051 | |
|
| 2.1806 | 0.63 | 2110000 | 0.5176 | 2.2051 | |
|
| 2.1832 | 0.63 | 2115000 | 0.5175 | 2.2051 | |
|
| 2.1766 | 0.64 | 2120000 | 0.5178 | 2.2031 | |
|
| 2.1775 | 0.64 | 2125000 | 0.5178 | 2.2031 | |
|
| 2.1801 | 0.64 | 2130000 | 0.5177 | 2.2031 | |
|
| 2.1789 | 0.64 | 2135000 | 0.5178 | 2.2031 | |
|
| 2.1794 | 0.64 | 2140000 | 0.5178 | 2.2031 | |
|
| 2.1799 | 0.64 | 2145000 | 0.5179 | 2.2012 | |
|
| 2.1746 | 0.64 | 2150000 | 0.5180 | 2.2012 | |
|
| 2.1766 | 0.65 | 2155000 | 0.5179 | 2.2012 | |
|
| 2.1754 | 0.65 | 2160000 | 0.5177 | 2.2012 | |
|
| 2.1764 | 0.65 | 2165000 | 0.5177 | 2.2012 | |
|
| 2.1745 | 0.65 | 2170000 | 0.5183 | 2.1992 | |
|
| 2.1735 | 0.65 | 2175000 | 0.5180 | 2.1992 | |
|
| 2.1778 | 0.65 | 2180000 | 0.5181 | 2.1992 | |
|
| 2.1717 | 0.65 | 2185000 | 0.5183 | 2.1992 | |
|
| 2.1752 | 0.66 | 2190000 | 0.5185 | 2.1973 | |
|
| 2.1747 | 0.66 | 2195000 | 0.5185 | 2.1973 | |
|
| 2.1754 | 0.66 | 2200000 | 0.5186 | 2.1973 | |
|
| 2.1728 | 0.66 | 2205000 | 0.5188 | 2.1973 | |
|
| 2.1684 | 0.66 | 2210000 | 0.5186 | 2.1973 | |
|
| 2.1722 | 0.66 | 2215000 | 0.5188 | 2.1953 | |
|
| 2.1692 | 0.67 | 2220000 | 0.5190 | 2.1953 | |
|
| 2.176 | 0.67 | 2225000 | 0.5191 | 2.1953 | |
|
| 2.1697 | 0.67 | 2230000 | 0.5190 | 2.1953 | |
|
| 2.1731 | 0.67 | 2235000 | 0.5191 | 2.1953 | |
|
| 2.173 | 0.67 | 2240000 | 0.5191 | 2.1934 | |
|
| 2.1714 | 0.67 | 2245000 | 0.5193 | 2.1934 | |
|
| 2.1719 | 0.67 | 2250000 | 0.5192 | 2.1934 | |
|
| 2.1667 | 0.68 | 2255000 | 0.5190 | 2.1934 | |
|
| 2.1653 | 0.68 | 2260000 | 0.5192 | 2.1934 | |
|
| 2.1656 | 0.68 | 2265000 | 0.5193 | 2.1914 | |
|
| 2.1695 | 0.68 | 2270000 | 0.5194 | 2.1914 | |
|
| 2.17 | 0.68 | 2275000 | 0.5196 | 2.1914 | |
|
| 2.1628 | 0.68 | 2280000 | 0.5197 | 2.1914 | |
|
| 2.1648 | 0.68 | 2285000 | 0.5196 | 2.1895 | |
|
| 2.1647 | 0.69 | 2290000 | 0.5199 | 2.1895 | |
|
| 2.1648 | 0.69 | 2295000 | 0.5198 | 2.1895 | |
|
| 2.168 | 0.69 | 2300000 | 0.5197 | 2.1895 | |
|
| 2.1607 | 0.69 | 2305000 | 0.5198 | 2.1895 | |
|
| 2.1674 | 0.69 | 2310000 | 0.5200 | 2.1875 | |
|
| 2.1656 | 0.69 | 2315000 | 0.5200 | 2.1875 | |
|
| 2.1637 | 0.7 | 2320000 | 0.5202 | 2.1875 | |
|
| 2.1649 | 0.7 | 2325000 | 0.5201 | 2.1875 | |
|
| 2.1625 | 0.7 | 2330000 | 0.5201 | 2.1875 | |
|
| 2.1627 | 0.7 | 2335000 | 0.5203 | 2.1875 | |
|
| 2.1598 | 0.7 | 2340000 | 0.5203 | 2.1855 | |
|
| 2.1638 | 0.7 | 2345000 | 0.5201 | 2.1875 | |
|
| 2.1588 | 0.7 | 2350000 | 0.5205 | 2.1855 | |
|
| 2.1633 | 0.71 | 2355000 | 0.5205 | 2.1855 | |
|
| 2.1621 | 0.71 | 2360000 | 0.5205 | 2.1855 | |
|
| 2.165 | 0.71 | 2365000 | 0.5207 | 2.1836 | |
|
| 2.159 | 0.71 | 2370000 | 0.5206 | 2.1836 | |
|
| 2.1573 | 0.71 | 2375000 | 0.5207 | 2.1836 | |
|
| 2.1556 | 0.71 | 2380000 | 0.5208 | 2.1836 | |
|
| 2.1562 | 0.71 | 2385000 | 0.5210 | 2.1836 | |
|
| 2.1572 | 0.72 | 2390000 | 0.5209 | 2.1836 | |
|
| 2.1577 | 0.72 | 2395000 | 0.5209 | 2.1816 | |
|
| 2.1529 | 0.72 | 2400000 | 0.5210 | 2.1816 | |
|
| 2.1636 | 0.72 | 2405000 | 0.5211 | 2.1816 | |
|
| 2.1521 | 0.72 | 2410000 | 0.5213 | 2.1816 | |
|
| 2.1574 | 0.72 | 2415000 | 0.5214 | 2.1816 | |
|
| 2.1546 | 0.72 | 2420000 | 0.5213 | 2.1797 | |
|
| 2.1572 | 0.73 | 2425000 | 0.5212 | 2.1797 | |
|
| 2.1544 | 0.73 | 2430000 | 0.5212 | 2.1797 | |
|
| 2.15 | 0.73 | 2435000 | 0.5213 | 2.1797 | |
|
| 2.1537 | 0.73 | 2440000 | 0.5217 | 2.1777 | |
|
| 2.1552 | 0.73 | 2445000 | 0.5216 | 2.1777 | |
|
| 2.1522 | 0.73 | 2450000 | 0.5215 | 2.1777 | |
|
| 2.1487 | 0.74 | 2455000 | 0.5215 | 2.1777 | |
|
| 2.1582 | 0.74 | 2460000 | 0.5215 | 2.1777 | |
|
| 2.1582 | 0.74 | 2465000 | 0.5218 | 2.1777 | |
|
| 2.1529 | 0.74 | 2470000 | 0.5218 | 2.1777 | |
|
| 2.1549 | 0.74 | 2475000 | 0.5219 | 2.1758 | |
|
| 2.1525 | 0.74 | 2480000 | 0.5219 | 2.1758 | |
|
| 2.1478 | 0.74 | 2485000 | 0.5221 | 2.1758 | |
|
| 2.1524 | 0.75 | 2490000 | 0.5220 | 2.1758 | |
|
| 2.1477 | 0.75 | 2495000 | 0.5220 | 2.1738 | |
|
| 2.1524 | 0.75 | 2500000 | 0.5222 | 2.1738 | |
|
| 2.147 | 0.75 | 2505000 | 0.5222 | 2.1738 | |
|
| 2.1481 | 0.75 | 2510000 | 0.5223 | 2.1738 | |
|
| 2.1494 | 0.75 | 2515000 | 0.5223 | 2.1738 | |
|
| 2.1484 | 0.75 | 2520000 | 0.5223 | 2.1738 | |
|
| 2.1474 | 0.76 | 2525000 | 0.5223 | 2.1738 | |
|
| 2.1487 | 0.76 | 2530000 | 0.5223 | 2.1738 | |
|
| 2.1465 | 0.76 | 2535000 | 0.5225 | 2.1719 | |
|
| 2.1456 | 0.76 | 2540000 | 0.5226 | 2.1719 | |
|
| 2.1482 | 0.76 | 2545000 | 0.5224 | 2.1719 | |
|
| 2.1451 | 0.76 | 2550000 | 0.5226 | 2.1719 | |
|
| 2.143 | 0.77 | 2555000 | 0.5226 | 2.1719 | |
|
| 2.1463 | 0.77 | 2560000 | 0.5225 | 2.1719 | |
|
| 2.1466 | 0.77 | 2565000 | 0.5228 | 2.1699 | |
|
| 2.1423 | 0.77 | 2570000 | 0.5229 | 2.1699 | |
|
| 2.1423 | 0.77 | 2575000 | 0.5231 | 2.1699 | |
|
| 2.1444 | 0.77 | 2580000 | 0.5230 | 2.1699 | |
|
| 2.1402 | 0.77 | 2585000 | 0.5230 | 2.1680 | |
|
| 2.1376 | 0.78 | 2590000 | 0.5231 | 2.1680 | |
|
| 2.1395 | 0.78 | 2595000 | 0.5232 | 2.1680 | |
|
| 2.1399 | 0.78 | 2600000 | 0.5233 | 2.1680 | |
|
| 2.1379 | 0.78 | 2605000 | 0.5231 | 2.1680 | |
|
| 2.1411 | 0.78 | 2610000 | 0.5234 | 2.1660 | |
|
| 2.1421 | 0.78 | 2615000 | 0.5232 | 2.1660 | |
|
| 2.1412 | 0.78 | 2620000 | 0.5237 | 2.1660 | |
|
| 2.1381 | 0.79 | 2625000 | 0.5236 | 2.1660 | |
|
| 2.142 | 0.79 | 2630000 | 0.5236 | 2.1660 | |
|
| 2.1394 | 0.79 | 2635000 | 0.5236 | 2.1641 | |
|
| 2.1384 | 0.79 | 2640000 | 0.5234 | 2.1641 | |
|
| 2.138 | 0.79 | 2645000 | 0.5236 | 2.1641 | |
|
| 2.1346 | 0.79 | 2650000 | 0.5239 | 2.1641 | |
|
| 2.1376 | 0.8 | 2655000 | 0.5239 | 2.1641 | |
|
| 2.1409 | 0.8 | 2660000 | 0.5240 | 2.1641 | |
|
| 2.1343 | 0.8 | 2665000 | 0.5240 | 2.1641 | |
|
| 2.1363 | 0.8 | 2670000 | 0.5240 | 2.1621 | |
|
| 2.1343 | 0.8 | 2675000 | 0.5242 | 2.1621 | |
|
| 2.1381 | 0.8 | 2680000 | 0.5243 | 2.1621 | |
|
| 2.1355 | 0.8 | 2685000 | 0.5241 | 2.1621 | |
|
| 2.1394 | 0.81 | 2690000 | 0.5242 | 2.1602 | |
|
| 2.1359 | 0.81 | 2695000 | 0.5245 | 2.1602 | |
|
| 2.1365 | 0.81 | 2700000 | 0.5244 | 2.1602 | |
|
| 2.131 | 0.81 | 2705000 | 0.5244 | 2.1602 | |
|
| 2.1337 | 0.81 | 2710000 | 0.5244 | 2.1602 | |
|
| 2.1307 | 0.81 | 2715000 | 0.5246 | 2.1582 | |
|
| 2.1333 | 0.81 | 2720000 | 0.5247 | 2.1582 | |
|
| 2.1354 | 0.82 | 2725000 | 0.5246 | 2.1582 | |
|
| 2.1372 | 0.82 | 2730000 | 0.5248 | 2.1582 | |
|
| 2.1323 | 0.82 | 2735000 | 0.5248 | 2.1582 | |
|
| 2.1315 | 0.82 | 2740000 | 0.5249 | 2.1562 | |
|
| 2.1341 | 0.82 | 2745000 | 0.5249 | 2.1562 | |
|
| 2.132 | 0.82 | 2750000 | 0.5250 | 2.1562 | |
|
| 2.1322 | 0.83 | 2755000 | 0.5252 | 2.1562 | |
|
| 2.1298 | 0.83 | 2760000 | 0.5252 | 2.1562 | |
|
| 2.1285 | 0.83 | 2765000 | 0.5252 | 2.1543 | |
|
| 2.1299 | 0.83 | 2770000 | 0.5252 | 2.1562 | |
|
| 2.1304 | 0.83 | 2775000 | 0.5253 | 2.1543 | |
|
| 2.1288 | 0.83 | 2780000 | 0.5254 | 2.1543 | |
|
| 2.1295 | 0.83 | 2785000 | 0.5253 | 2.1543 | |
|
| 2.129 | 0.84 | 2790000 | 0.5255 | 2.1543 | |
|
| 2.1285 | 0.84 | 2795000 | 0.5254 | 2.1543 | |
|
| 2.1292 | 0.84 | 2800000 | 0.5253 | 2.1543 | |
|
| 2.1278 | 0.84 | 2805000 | 0.5256 | 2.1523 | |
|
| 2.1239 | 0.84 | 2810000 | 0.5255 | 2.1523 | |
|
| 2.1241 | 0.84 | 2815000 | 0.5259 | 2.1523 | |
|
| 2.1232 | 0.84 | 2820000 | 0.5257 | 2.1523 | |
|
| 2.1241 | 0.85 | 2825000 | 0.5257 | 2.1504 | |
|
| 2.1236 | 0.85 | 2830000 | 0.5259 | 2.1504 | |
|
| 2.1272 | 0.85 | 2835000 | 0.5259 | 2.1504 | |
|
| 2.1271 | 0.85 | 2840000 | 0.5261 | 2.1504 | |
|
| 2.1249 | 0.85 | 2845000 | 0.5262 | 2.1484 | |
|
| 2.1245 | 0.85 | 2850000 | 0.5260 | 2.1484 | |
|
| 2.1222 | 0.86 | 2855000 | 0.5261 | 2.1484 | |
|
| 2.125 | 0.86 | 2860000 | 0.5263 | 2.1484 | |
|
| 2.1261 | 0.86 | 2865000 | 0.5261 | 2.1484 | |
|
| 2.1247 | 0.86 | 2870000 | 0.5262 | 2.1484 | |
|
| 2.1225 | 0.86 | 2875000 | 0.5263 | 2.1484 | |
|
| 2.122 | 0.86 | 2880000 | 0.5261 | 2.1484 | |
|
| 2.1237 | 0.86 | 2885000 | 0.5261 | 2.1465 | |
|
| 2.1219 | 0.87 | 2890000 | 0.5262 | 2.1465 | |
|
| 2.1248 | 0.87 | 2895000 | 0.5262 | 2.1465 | |
|
| 2.1191 | 0.87 | 2900000 | 0.5264 | 2.1465 | |
|
| 2.1181 | 0.87 | 2905000 | 0.5264 | 2.1465 | |
|
| 2.1176 | 0.87 | 2910000 | 0.5263 | 2.1465 | |
|
| 2.1191 | 0.87 | 2915000 | 0.5267 | 2.1465 | |
|
| 2.1206 | 0.87 | 2920000 | 0.5268 | 2.1445 | |
|
| 2.1148 | 0.88 | 2925000 | 0.5267 | 2.1445 | |
|
| 2.1188 | 0.88 | 2930000 | 0.5270 | 2.1445 | |
|
| 2.1118 | 0.88 | 2935000 | 0.5270 | 2.1445 | |
|
| 2.1283 | 0.88 | 2940000 | 0.5244 | 2.1582 | |
|
| 2.1336 | 0.88 | 2945000 | 0.5240 | 2.1621 | |
|
| 2.1311 | 0.88 | 2950000 | 0.5237 | 2.1621 | |
|
| 2.1377 | 0.89 | 2955000 | 0.5236 | 2.1641 | |
|
| 2.136 | 0.89 | 2960000 | 0.5236 | 2.1641 | |
|
| 2.1394 | 0.89 | 2965000 | 0.5233 | 2.1641 | |
|
| 2.1405 | 0.89 | 2970000 | 0.5233 | 2.1660 | |
|
| 2.1391 | 0.89 | 2975000 | 0.5236 | 2.1660 | |
|
| 2.1353 | 0.89 | 2980000 | 0.5234 | 2.1660 | |
|
| 2.1392 | 0.89 | 2985000 | 0.5234 | 2.1660 | |
|
| 2.1384 | 0.9 | 2990000 | 0.5235 | 2.1660 | |
|
| 2.1373 | 0.9 | 2995000 | 0.5233 | 2.1660 | |
|
| 2.1346 | 0.9 | 3000000 | 0.5234 | 2.1660 | |
|
| 2.1368 | 0.9 | 3005000 | 0.5235 | 2.1660 | |
|
| 2.1383 | 0.9 | 3010000 | 0.5233 | 2.1660 | |
|
| 2.1447 | 0.9 | 3015000 | 0.5233 | 2.1660 | |
|
| 2.1392 | 0.9 | 3020000 | 0.5234 | 2.1660 | |
|
| 2.1359 | 0.91 | 3025000 | 0.5233 | 2.1660 | |
|
| 2.1408 | 0.91 | 3030000 | 0.5233 | 2.1660 | |
|
| 2.1437 | 0.91 | 3035000 | 0.5233 | 2.1660 | |
|
| 2.1354 | 0.91 | 3040000 | 0.5233 | 2.1660 | |
|
| 2.1371 | 0.91 | 3045000 | 0.5235 | 2.1660 | |
|
| 2.1399 | 0.91 | 3050000 | 0.5234 | 2.1660 | |
|
| 2.1387 | 0.92 | 3055000 | 0.5234 | 2.1660 | |
|
| 2.1406 | 0.92 | 3060000 | 0.5232 | 2.1660 | |
|
| 2.1387 | 0.92 | 3065000 | 0.5235 | 2.1660 | |
|
| 2.1413 | 0.92 | 3070000 | 0.5235 | 2.1660 | |
|
| 2.1371 | 0.92 | 3075000 | 0.5235 | 2.1641 | |
|
| 2.138 | 0.92 | 3080000 | 0.5235 | 2.1641 | |
|
| 2.1385 | 0.92 | 3085000 | 0.5236 | 2.1641 | |
|
| 2.135 | 0.93 | 3090000 | 0.5234 | 2.1660 | |
|
| 2.1401 | 0.93 | 3095000 | 0.5236 | 2.1641 | |
|
| 2.1374 | 0.93 | 3100000 | 0.5236 | 2.1641 | |
|
| 2.1358 | 0.93 | 3105000 | 0.5237 | 2.1641 | |
|
| 2.1344 | 0.93 | 3110000 | 0.5239 | 2.1621 | |
|
| 2.1368 | 0.93 | 3115000 | 0.5239 | 2.1621 | |
|
| 2.1345 | 0.93 | 3120000 | 0.5237 | 2.1621 | |
|
| 2.1358 | 0.94 | 3125000 | 0.5239 | 2.1621 | |
|
| 2.1395 | 0.94 | 3130000 | 0.5239 | 2.1621 | |
|
| 2.1359 | 0.94 | 3135000 | 0.5243 | 2.1621 | |
|
| 2.1373 | 0.94 | 3140000 | 0.5242 | 2.1602 | |
|
| 2.1357 | 0.94 | 3145000 | 0.5243 | 2.1602 | |
|
| 2.1354 | 0.94 | 3150000 | 0.5244 | 2.1602 | |
|
| 2.1323 | 0.95 | 3155000 | 0.5244 | 2.1602 | |
|
| 2.133 | 0.95 | 3160000 | 0.5242 | 2.1602 | |
|
| 2.1315 | 0.95 | 3165000 | 0.5244 | 2.1602 | |
|
| 2.1363 | 0.95 | 3170000 | 0.5243 | 2.1602 | |
|
| 2.1349 | 0.95 | 3175000 | 0.5245 | 2.1602 | |
|
| 2.1336 | 0.95 | 3180000 | 0.5244 | 2.1602 | |
|
| 2.1364 | 0.95 | 3185000 | 0.5244 | 2.1582 | |
|
| 2.133 | 0.96 | 3190000 | 0.5243 | 2.1582 | |
|
| 2.1349 | 0.96 | 3195000 | 0.5245 | 2.1582 | |
|
| 2.134 | 0.96 | 3200000 | 0.5246 | 2.1582 | |
|
| 2.1308 | 0.96 | 3205000 | 0.5249 | 2.1562 | |
|
| 2.1302 | 0.96 | 3210000 | 0.5247 | 2.1562 | |
|
| 2.1302 | 0.96 | 3215000 | 0.5247 | 2.1562 | |
|
| 2.1331 | 0.96 | 3220000 | 0.5248 | 2.1562 | |
|
| 2.1273 | 0.97 | 3225000 | 0.5247 | 2.1562 | |
|
| 2.1286 | 0.97 | 3230000 | 0.5250 | 2.1562 | |
|
| 2.1282 | 0.97 | 3235000 | 0.5250 | 2.1543 | |
|
| 2.1309 | 0.97 | 3240000 | 0.5251 | 2.1543 | |
|
| 2.1295 | 0.97 | 3245000 | 0.5254 | 2.1543 | |
|
| 2.1275 | 0.97 | 3250000 | 0.5254 | 2.1543 | |
|
| 2.133 | 0.98 | 3255000 | 0.5254 | 2.1543 | |
|
| 2.1301 | 0.98 | 3260000 | 0.5251 | 2.1543 | |
|
| 2.1314 | 0.98 | 3265000 | 0.5253 | 2.1523 | |
|
| 2.1258 | 0.98 | 3270000 | 0.5255 | 2.1523 | |
|
| 2.1286 | 0.98 | 3275000 | 0.5254 | 2.1523 | |
|
| 2.1267 | 0.98 | 3280000 | 0.5254 | 2.1523 | |
|
| 2.13 | 0.98 | 3285000 | 0.5254 | 2.1523 | |
|
| 2.1284 | 0.99 | 3290000 | 0.5255 | 2.1523 | |
|
| 2.1295 | 0.99 | 3295000 | 0.5254 | 2.1523 | |
|
| 2.1241 | 0.99 | 3300000 | 0.5256 | 2.1523 | |
|
| 2.1297 | 0.99 | 3305000 | 0.5258 | 2.1523 | |
|
| 2.126 | 0.99 | 3310000 | 0.5256 | 2.1504 | |
|
| 2.1263 | 0.99 | 3315000 | 0.5256 | 2.1504 | |
|
| 2.1273 | 0.99 | 3320000 | 0.5256 | 2.1504 | |
|
| 2.1214 | 1.0 | 3325000 | 0.5255 | 2.1504 | |
|
| 2.1275 | 1.0 | 3330000 | 0.5256 | 2.1504 | |
|
| 2.1227 | 1.0 | 3335000 | 0.5258 | 2.1504 | |
|
|
|
|
|
## Eval results |
|
|
|
It achieves the following results on the evaluation set: |
|
- Loss: 2.1504 |
|
- Accuracy: 0.5258 |
|
|
|
### Framework versions |
|
|
|
- Transformers 4.30.2 |
|
- Pytorch 2.0.0 |
|
- Datasets 2.13.1 |
|
- Tokenizers 0.13.3 |
