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--- |
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license: apache-2.0 |
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base_model: t5-base |
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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: T5_base_title |
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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_base_title |
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This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.0487 |
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- Rouge1: 0.3848 |
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- Rouge2: 0.1901 |
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- Rougel: 0.3297 |
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- Rougelsum: 0.3288 |
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- Gen Len: 16.795 |
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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: 10 |
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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 | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| |
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| No log | 1.0 | 200 | 2.0966 | 0.3525 | 0.165 | 0.2921 | 0.2934 | 17.4 | |
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| No log | 2.0 | 400 | 2.0533 | 0.3706 | 0.1775 | 0.3145 | 0.3147 | 16.52 | |
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| 2.2032 | 3.0 | 600 | 2.0453 | 0.3754 | 0.1867 | 0.3226 | 0.3227 | 16.68 | |
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| 2.2032 | 4.0 | 800 | 2.0383 | 0.379 | 0.1887 | 0.3246 | 0.3243 | 16.36 | |
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| 1.8535 | 5.0 | 1000 | 2.0376 | 0.3849 | 0.1881 | 0.3269 | 0.3267 | 16.755 | |
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| 1.8535 | 6.0 | 1200 | 2.0416 | 0.378 | 0.1792 | 0.3236 | 0.3228 | 16.84 | |
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| 1.8535 | 7.0 | 1400 | 2.0445 | 0.3805 | 0.1848 | 0.3249 | 0.3248 | 16.65 | |
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| 1.692 | 8.0 | 1600 | 2.0484 | 0.3876 | 0.187 | 0.3289 | 0.3285 | 16.845 | |
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| 1.692 | 9.0 | 1800 | 2.0473 | 0.3891 | 0.1912 | 0.3325 | 0.332 | 16.815 | |
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| 1.6276 | 10.0 | 2000 | 2.0487 | 0.3848 | 0.1901 | 0.3297 | 0.3288 | 16.795 | |
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### Framework versions |
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- Transformers 4.37.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.17.0 |
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- Tokenizers 0.15.2 |
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