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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: 21.6196 |
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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: 2.1466 |
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- Rouge1: 21.6196 |
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- Rouge2: 7.7979 |
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- Rougel: 17.5683 |
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- Rougelsum: 17.6757 |
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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: 4 |
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- eval_batch_size: 4 |
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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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| 3.9629 | 1.0 | 2170 | 2.3132 | 20.7316 | 7.3431 | 16.9157 | 17.0149 | |
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| 2.9704 | 2.0 | 4340 | 2.2299 | 21.3148 | 7.8529 | 17.2968 | 17.3873 | |
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| 2.8026 | 3.0 | 6510 | 2.2092 | 21.3313 | 7.8526 | 17.3679 | 17.4773 | |
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| 2.7054 | 4.0 | 8680 | 2.1876 | 21.6909 | 7.9841 | 17.6881 | 17.7839 | |
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| 2.6453 | 5.0 | 10850 | 2.1743 | 21.7372 | 7.7546 | 17.6551 | 17.7575 | |
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| 2.5925 | 6.0 | 13020 | 2.1602 | 21.5715 | 7.7879 | 17.5943 | 17.6994 | |
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| 2.5619 | 7.0 | 15190 | 2.1482 | 21.5888 | 7.8789 | 17.6519 | 17.752 | |
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| 2.5415 | 8.0 | 17360 | 2.1466 | 21.6196 | 7.7979 | 17.5683 | 17.6757 | |
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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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