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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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- summarization |
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- generated_from_trainer |
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metrics: |
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- rouge |
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model-index: |
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- name: mt5-small-finetuned-amazon-en-es |
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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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# mt5-small-finetuned-amazon-en-es |
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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: 3.0280 |
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- Rouge1: 17.3563 |
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- Rouge2: 8.6193 |
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- Rougel: 17.081 |
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- Rougelsum: 17.1297 |
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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: 5.6e-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: 8 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:| |
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| 7.0507 | 1.0 | 1209 | 3.3225 | 12.6324 | 4.7979 | 12.3957 | 12.4312 | |
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| 3.9068 | 2.0 | 2418 | 3.1852 | 16.432 | 8.2165 | 15.7321 | 15.789 | |
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| 3.5973 | 3.0 | 3627 | 3.0834 | 16.912 | 8.2736 | 16.3027 | 16.3174 | |
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| 3.4111 | 4.0 | 4836 | 3.0560 | 16.8768 | 8.0417 | 16.209 | 16.2473 | |
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| 3.318 | 5.0 | 6045 | 3.0464 | 17.5367 | 8.364 | 16.9286 | 16.9249 | |
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| 3.2435 | 6.0 | 7254 | 3.0371 | 17.3217 | 8.398 | 16.9066 | 17.0021 | |
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| 3.202 | 7.0 | 8463 | 3.0347 | 17.1712 | 8.0887 | 16.7378 | 16.748 | |
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| 3.1799 | 8.0 | 9672 | 3.0280 | 17.3563 | 8.6193 | 17.081 | 17.1297 | |
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### Framework versions |
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- Transformers 4.33.2 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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