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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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- xlsum |
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metrics: |
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- rouge |
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model-index: |
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- name: mt5-small-finetuned-summary |
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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: xlsum |
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type: xlsum |
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config: french |
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split: validation |
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args: french |
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metrics: |
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- name: Rouge1 |
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type: rouge |
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value: 22.1761 |
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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-summary |
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This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the xlsum dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.2770 |
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- Rouge1: 22.1761 |
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- Rouge2: 8.0115 |
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- Rougel: 18.8245 |
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- Rougelsum: 18.8574 |
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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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| 4.7862 | 1.0 | 1085 | 2.5085 | 21.2935 | 7.4006 | 18.0791 | 18.0868 | |
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| 3.2212 | 2.0 | 2170 | 2.4069 | 21.968 | 7.9139 | 18.5785 | 18.6248 | |
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| 3.0201 | 3.0 | 3255 | 2.3489 | 21.8529 | 7.9865 | 18.6842 | 18.7074 | |
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| 2.9085 | 4.0 | 4340 | 2.3173 | 22.1605 | 8.2646 | 18.8284 | 18.838 | |
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| 2.8285 | 5.0 | 5425 | 2.2965 | 22.0612 | 8.0447 | 18.7454 | 18.7784 | |
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| 2.7727 | 6.0 | 6510 | 2.2899 | 22.1416 | 7.9747 | 18.7622 | 18.8029 | |
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| 2.7311 | 7.0 | 7595 | 2.2797 | 22.2979 | 8.1382 | 18.9798 | 19.035 | |
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| 2.7171 | 8.0 | 8680 | 2.2770 | 22.1761 | 8.0115 | 18.8245 | 18.8574 | |
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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 2.15.0 |
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- Tokenizers 0.15.0 |
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