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--- |
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license: apache-2.0 |
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base_model: LinhCT/mt5-small-finetuned-amazon-en-es |
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tags: |
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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-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-finetuned-amazon-en-es |
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This model is a fine-tuned version of [LinhCT/mt5-small-finetuned-amazon-en-es](https://huggingface.co/LinhCT/mt5-small-finetuned-amazon-en-es) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.4243 |
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- Rouge1: 28.2282 |
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- Rouge2: 13.0079 |
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- Rougel: 27.8476 |
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- Rougelsum: 27.9373 |
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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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| 5.1931 | 1.0 | 1152 | 3.7893 | 19.9416 | 8.7882 | 19.7175 | 19.6944 | |
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| 4.2391 | 2.0 | 2304 | 3.6033 | 24.7762 | 11.4627 | 24.5132 | 24.5349 | |
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| 3.9401 | 3.0 | 3456 | 3.5088 | 25.618 | 11.8757 | 25.316 | 25.3784 | |
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| 3.7617 | 4.0 | 4608 | 3.4602 | 26.2721 | 11.8065 | 25.9693 | 26.0518 | |
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| 3.6381 | 5.0 | 5760 | 3.4439 | 27.3459 | 12.668 | 26.9862 | 27.0528 | |
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| 3.548 | 6.0 | 6912 | 3.4317 | 27.751 | 12.7711 | 27.3445 | 27.3912 | |
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| 3.4956 | 7.0 | 8064 | 3.4343 | 28.7685 | 13.1835 | 28.3702 | 28.4383 | |
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| 3.4589 | 8.0 | 9216 | 3.4243 | 28.2282 | 13.0079 | 27.8476 | 27.9373 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.2 |
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- Tokenizers 0.19.1 |
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