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---
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library_name: transformers
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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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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: 2.0229
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- Bertscore Precision: 0.7189
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- Bertscore Recall: 0.6939
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- Bertscore F1: 0.7056
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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: 24
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- eval_batch_size: 24
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- seed: 42
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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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 | Bertscore Precision | Bertscore Recall | Bertscore F1 |
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|:-------------:|:-----:|:-----:|:---------------:|:-------------------:|:----------------:|:------------:|
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| 2.5119 | 1.0 | 1557 | 2.2031 | 0.711 | 0.6852 | 0.6972 |
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| 2.5009 | 2.0 | 3114 | 2.1234 | 0.7154 | 0.6875 | 0.7005 |
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| 2.4158 | 3.0 | 4671 | 2.0854 | 0.7165 | 0.6914 | 0.7032 |
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| 2.3603 | 4.0 | 6228 | 2.0629 | 0.7166 | 0.6911 | 0.703 |
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| 2.3206 | 5.0 | 7785 | 2.0451 | 0.7191 | 0.6934 | 0.7054 |
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| 2.2938 | 6.0 | 9342 | 2.0328 | 0.718 | 0.6934 | 0.7049 |
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| 2.2718 | 7.0 | 10899 | 2.0253 | 0.7191 | 0.6944 | 0.706 |
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| 2.2622 | 8.0 | 12456 | 2.0229 | 0.7189 | 0.6939 | 0.7056 |
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### Framework versions
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- Transformers 4.48.3
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- Pytorch 2.7.1+cu118
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- Datasets 2.14.6
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- Tokenizers 0.21.1
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