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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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metrics: |
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- bleu |
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model-index: |
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- name: md_mt5_1511_v8 |
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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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# md_mt5_1511_v8 |
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This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3865 |
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- Bleu: 0.6474 |
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- Gen Len: 18.7566 |
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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: 2e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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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: 15 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len | |
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|:-------------:|:-----:|:-----:|:---------------:|:------:|:-------:| |
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| 5.2266 | 1.0 | 1250 | 2.0508 | 0.8851 | 16.8074 | |
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| 1.9533 | 2.0 | 2500 | 1.1931 | 1.1725 | 18.8668 | |
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| 1.5627 | 3.0 | 3750 | 0.8881 | 0.6185 | 18.672 | |
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| 1.237 | 4.0 | 5000 | 0.7267 | 0.6301 | 18.7212 | |
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| 1.1021 | 5.0 | 6250 | 0.6370 | 0.6165 | 18.679 | |
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| 0.962 | 6.0 | 7500 | 0.5726 | 0.5885 | 18.7398 | |
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| 0.8972 | 7.0 | 8750 | 0.5235 | 0.6011 | 18.7622 | |
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| 0.8385 | 8.0 | 10000 | 0.4881 | 0.6087 | 18.761 | |
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| 0.7949 | 9.0 | 11250 | 0.4579 | 0.6185 | 18.7696 | |
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| 0.7482 | 10.0 | 12500 | 0.4342 | 0.6175 | 18.755 | |
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| 0.7304 | 11.0 | 13750 | 0.4159 | 0.631 | 18.7478 | |
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| 0.7009 | 12.0 | 15000 | 0.4029 | 0.6373 | 18.7532 | |
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| 0.6863 | 13.0 | 16250 | 0.3938 | 0.6434 | 18.7546 | |
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| 0.6841 | 14.0 | 17500 | 0.3882 | 0.6464 | 18.7512 | |
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| 0.6749 | 15.0 | 18750 | 0.3865 | 0.6474 | 18.7566 | |
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### Framework versions |
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- Transformers 4.35.1 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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