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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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- wcep-10 |
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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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- 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: wcep-10 |
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type: wcep-10 |
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config: roberta |
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split: validation |
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args: roberta |
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metrics: |
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- name: Rouge1 |
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type: rouge |
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value: 22.6862 |
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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 wcep-10 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.1575 |
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- Rouge1: 22.6862 |
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- Rouge2: 7.7268 |
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- Rougel: 19.1961 |
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- Rougelsum: 19.3808 |
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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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| 6.5905 | 1.0 | 1020 | 3.4711 | 21.2268 | 7.4345 | 18.5023 | 18.6264 | |
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| 4.1604 | 2.0 | 2040 | 3.3228 | 21.6354 | 7.3939 | 18.4926 | 18.6047 | |
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| 3.914 | 3.0 | 3060 | 3.2606 | 21.9787 | 7.5818 | 18.6971 | 18.8603 | |
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| 3.7698 | 4.0 | 4080 | 3.2058 | 21.8859 | 7.5625 | 18.6413 | 18.8169 | |
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| 3.679 | 5.0 | 5100 | 3.1824 | 22.6515 | 7.7467 | 19.1196 | 19.3121 | |
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| 3.6131 | 6.0 | 6120 | 3.1678 | 22.0223 | 7.6153 | 18.7956 | 18.9968 | |
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| 3.5722 | 7.0 | 7140 | 3.1631 | 22.679 | 7.7952 | 19.1784 | 19.384 | |
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| 3.5432 | 8.0 | 8160 | 3.1575 | 22.6862 | 7.7268 | 19.1961 | 19.3808 | |
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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 2.20.0 |
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- Tokenizers 0.19.1 |
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