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--- |
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license: apache-2.0 |
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base_model: distilbert-base-multilingual-cased |
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tags: |
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- generated_from_trainer |
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metrics: |
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- precision |
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- recall |
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- f1 |
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- accuracy |
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model-index: |
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- name: NLP-HIBA2_DisTEMIST_fine_tuned_DistilBERT-pretrained-model |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# NLP-HIBA2_DisTEMIST_fine_tuned_DistilBERT-pretrained-model |
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This model is a fine-tuned version of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2224 |
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- Precision: 0.5553 |
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- Recall: 0.5163 |
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- F1: 0.5351 |
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- Accuracy: 0.9502 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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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: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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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: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| No log | 1.0 | 71 | 0.1767 | 0.4612 | 0.4905 | 0.4754 | 0.9399 | |
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| No log | 2.0 | 142 | 0.1696 | 0.5173 | 0.4400 | 0.4755 | 0.9481 | |
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| No log | 3.0 | 213 | 0.1782 | 0.5189 | 0.5290 | 0.5239 | 0.9485 | |
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| No log | 4.0 | 284 | 0.1928 | 0.5275 | 0.4988 | 0.5128 | 0.9475 | |
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| No log | 5.0 | 355 | 0.2020 | 0.5800 | 0.4782 | 0.5242 | 0.9512 | |
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| No log | 6.0 | 426 | 0.2091 | 0.5645 | 0.4849 | 0.5217 | 0.9506 | |
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| No log | 7.0 | 497 | 0.2035 | 0.5608 | 0.5095 | 0.5339 | 0.9511 | |
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| 0.0531 | 8.0 | 568 | 0.2150 | 0.5282 | 0.5385 | 0.5333 | 0.9484 | |
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| 0.0531 | 9.0 | 639 | 0.2224 | 0.5639 | 0.5068 | 0.5338 | 0.9507 | |
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| 0.0531 | 10.0 | 710 | 0.2224 | 0.5553 | 0.5163 | 0.5351 | 0.9502 | |
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### Framework versions |
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- Transformers 4.34.0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.14.1 |
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