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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-t5/t5-small |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: T5_small_fine_tuned |
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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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# T5_small_fine_tuned |
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This model is a fine-tuned version of [google-t5/t5-small](https://huggingface.co/google-t5/t5-small) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.6491 |
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- Rougel Fmeasure: 0.1247 |
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- Bertscore F1: -0.0215 |
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- Combined Score: 0.0516 |
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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: 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: 4 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rougel Fmeasure | Bertscore F1 | Combined Score | |
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|:-------------:|:-----:|:----:|:---------------:|:---------------:|:------------:|:--------------:| |
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| 1.9205 | 1.0 | 2369 | 2.6825 | 0.113 | -0.0448 | 0.0341 | |
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| 1.8233 | 2.0 | 4738 | 2.6561 | 0.1227 | -0.0249 | 0.0489 | |
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| 1.7693 | 3.0 | 7107 | 2.6505 | 0.1246 | -0.0215 | 0.0515 | |
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| 1.7611 | 4.0 | 9476 | 2.6491 | 0.1247 | -0.0215 | 0.0516 | |
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### Framework versions |
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- Transformers 4.46.2 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.3 |
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