chunwoolee0
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End of training
Browse files- README.md +86 -0
- generation_config.json +6 -0
README.md
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---
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license: apache-2.0
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base_model: google/mt5-small
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tags:
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- generated_from_trainer
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datasets:
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- wmt16
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metrics:
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- rouge
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- sacrebleu
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model-index:
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- name: mt5_small_wmt16_de_en
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results:
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- task:
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name: Sequence-to-sequence Language Modeling
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type: text2text-generation
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dataset:
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name: wmt16
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type: wmt16
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config: de-en
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split: validation
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args: de-en
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metrics:
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- name: Rouge1
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type: rouge
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value: 0.3666
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- name: Sacrebleu
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type: sacrebleu
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value: 6.4622
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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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# mt5_small_wmt16_de_en
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This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the wmt16 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.4612
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- Rouge1: 0.3666
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- Rouge2: 0.147
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- Rougel: 0.3362
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- Sacrebleu: 6.4622
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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: 0.0005
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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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- gradient_accumulation_steps: 8
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- total_train_batch_size: 64
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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: 5
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Sacrebleu |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
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| 3.3059 | 1.6 | 500 | 2.5597 | 0.3398 | 0.1261 | 0.3068 | 5.5524 |
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| 2.4093 | 3.2 | 1000 | 2.4996 | 0.3609 | 0.144 | 0.3304 | 6.2002 |
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| 2.2322 | 4.8 | 1500 | 2.4612 | 0.3666 | 0.147 | 0.3362 | 6.4622 |
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### Framework versions
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- Transformers 4.32.0
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- Pytorch 2.0.1+cu118
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- Datasets 2.14.4
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- Tokenizers 0.13.3
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generation_config.json
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{
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"decoder_start_token_id": 0,
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"eos_token_id": 1,
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"pad_token_id": 0,
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"transformers_version": "4.32.0"
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}
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