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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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datasets: |
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- gazeta |
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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: gazeta |
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type: gazeta |
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config: default |
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split: validation |
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args: default |
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metrics: |
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- name: Rouge1 |
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type: rouge |
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value: 9.9348 |
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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 gazeta dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.2573 |
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- Rouge1: 9.9348 |
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- Rouge2: 1.4701 |
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- Rougel: 9.7352 |
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- Rougelsum: 9.7173 |
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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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| 5.0727 | 1.0 | 763 | 2.4238 | 9.9038 | 2.2835 | 9.5715 | 9.6056 | |
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| 3.4561 | 2.0 | 1526 | 2.3779 | 10.5328 | 2.1668 | 10.297 | 10.2517 | |
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| 3.2731 | 3.0 | 2289 | 2.3248 | 11.0603 | 2.3552 | 10.9513 | 10.9458 | |
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| 3.1629 | 4.0 | 3052 | 2.2993 | 9.6206 | 1.553 | 9.4704 | 9.4079 | |
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| 3.0912 | 5.0 | 3815 | 2.2779 | 9.9379 | 1.5493 | 9.7858 | 9.7129 | |
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| 3.0449 | 6.0 | 4578 | 2.2698 | 10.1558 | 1.5231 | 9.947 | 9.8629 | |
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| 3.0184 | 7.0 | 5341 | 2.2683 | 9.7056 | 1.5373 | 9.4965 | 9.3964 | |
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| 2.9987 | 8.0 | 6104 | 2.2573 | 9.9348 | 1.4701 | 9.7352 | 9.7173 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.17.0 |
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- Tokenizers 0.15.1 |
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