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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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metrics: |
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- rouge |
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model-index: |
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- name: mt5-small-sport |
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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-small-sport |
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This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.2444 |
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- Rouge1: 22.6291 |
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- Rouge2: 9.9519 |
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- Rougel: 18.0362 |
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- Rougelsum: 19.4768 |
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- Gen Len: 19.0 |
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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: 2e-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: 16 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
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|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:| |
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| 2.3085 | 1.0 | 2897 | 1.6680 | 21.9624 | 8.3028 | 16.8626 | 18.4892 | 19.0 | |
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| 1.9601 | 2.0 | 5794 | 1.5129 | 22.355 | 8.0976 | 17.1001 | 18.4518 | 19.0 | |
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| 1.8149 | 3.0 | 8691 | 1.4461 | 21.7553 | 8.2693 | 16.8813 | 18.1753 | 19.0 | |
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| 1.6939 | 4.0 | 11588 | 1.3859 | 22.1485 | 8.5444 | 17.1957 | 18.5641 | 19.0 | |
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| 1.6661 | 5.0 | 14485 | 1.3600 | 22.1464 | 8.5701 | 17.1911 | 18.5834 | 19.0 | |
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| 1.5776 | 6.0 | 17382 | 1.3366 | 22.188 | 8.6102 | 17.2114 | 18.6171 | 19.0 | |
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| 1.5635 | 7.0 | 20279 | 1.3036 | 22.2216 | 8.8053 | 17.3255 | 18.7127 | 19.0 | |
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| 1.5286 | 8.0 | 23176 | 1.2969 | 22.6098 | 9.4618 | 17.7417 | 19.2344 | 19.0 | |
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| 1.5034 | 9.0 | 26073 | 1.2774 | 22.7211 | 9.8323 | 17.9709 | 19.456 | 19.0 | |
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| 1.4808 | 10.0 | 28970 | 1.2697 | 22.6057 | 9.778 | 17.9176 | 19.3593 | 19.0 | |
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| 1.468 | 11.0 | 31867 | 1.2612 | 22.6437 | 9.8167 | 17.9253 | 19.3505 | 19.0 | |
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| 1.458 | 12.0 | 34764 | 1.2527 | 22.744 | 10.0172 | 18.0459 | 19.5324 | 19.0 | |
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| 1.4494 | 13.0 | 37661 | 1.2491 | 22.687 | 9.9128 | 17.9941 | 19.4752 | 19.0 | |
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| 1.4286 | 14.0 | 40558 | 1.2490 | 22.6855 | 9.9731 | 18.0414 | 19.5128 | 19.0 | |
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| 1.4448 | 15.0 | 43455 | 1.2436 | 22.6476 | 9.9704 | 18.0385 | 19.498 | 19.0 | |
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| 1.4324 | 16.0 | 46352 | 1.2444 | 22.6291 | 9.9519 | 18.0362 | 19.4768 | 19.0 | |
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### Framework versions |
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- Transformers 4.38.1 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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