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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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metrics: |
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- rouge |
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model-index: |
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- name: mt5-smallmt5-finetuned-on-en-yor-BBC-news |
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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-smallmt5-finetuned-on-en-yor-BBC-news |
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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: 2.9640 |
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- Rouge1: 31.9414 |
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- Rouge2: 10.6476 |
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- Rougel: 27.9541 |
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- Rougelsum: 27.974 |
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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: Use 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 | Rouge1 | Rouge2 | Rougel | Rougelsum | |
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|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:| |
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| 3.547 | 1.0 | 1588 | 3.2871 | 30.6764 | 9.756 | 26.925 | 26.9536 | |
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| 3.6705 | 2.0 | 3176 | 3.1250 | 30.387 | 9.6758 | 26.7739 | 26.8351 | |
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| 3.4985 | 3.0 | 4764 | 3.0648 | 31.2651 | 10.2554 | 27.4377 | 27.4828 | |
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| 3.3861 | 4.0 | 6352 | 3.0187 | 31.0368 | 10.0801 | 27.1596 | 27.1924 | |
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| 3.3116 | 5.0 | 7940 | 3.0051 | 31.9967 | 10.6125 | 28.0438 | 28.08 | |
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| 3.2603 | 6.0 | 9528 | 2.9801 | 31.7684 | 10.6465 | 27.8597 | 27.8956 | |
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| 3.2242 | 7.0 | 11116 | 2.9681 | 31.6692 | 10.4338 | 27.7238 | 27.7438 | |
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| 3.2007 | 8.0 | 12704 | 2.9640 | 31.9414 | 10.6476 | 27.9541 | 27.974 | |
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### Framework versions |
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- Transformers 4.47.1 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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