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--- |
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license: apache-2.0 |
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base_model: t5-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: T5_small_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_small_title |
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This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.4558 |
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- Rouge1: 0.316 |
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- Rouge2: 0.1498 |
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- Rougel: 0.2735 |
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- Rougelsum: 0.2728 |
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- Gen Len: 16.495 |
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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: 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 | 100 | 2.8637 | 0.2464 | 0.093 | 0.207 | 0.2066 | 18.87 | |
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| No log | 2.0 | 200 | 2.6086 | 0.2702 | 0.1142 | 0.2303 | 0.2299 | 18.475 | |
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| No log | 3.0 | 300 | 2.5391 | 0.2943 | 0.1373 | 0.2572 | 0.2565 | 17.44 | |
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| No log | 4.0 | 400 | 2.5082 | 0.2997 | 0.1421 | 0.2636 | 0.2629 | 17.02 | |
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| 2.8756 | 5.0 | 500 | 2.4853 | 0.3111 | 0.145 | 0.271 | 0.2701 | 16.755 | |
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| 2.8756 | 6.0 | 600 | 2.4729 | 0.3165 | 0.1501 | 0.2753 | 0.2745 | 16.555 | |
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| 2.8756 | 7.0 | 700 | 2.4635 | 0.3215 | 0.1533 | 0.2771 | 0.2768 | 16.51 | |
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| 2.8756 | 8.0 | 800 | 2.4601 | 0.3224 | 0.154 | 0.2773 | 0.2776 | 16.38 | |
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| 2.8756 | 9.0 | 900 | 2.4569 | 0.3167 | 0.1505 | 0.274 | 0.2733 | 16.495 | |
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| 2.5758 | 10.0 | 1000 | 2.4558 | 0.316 | 0.1498 | 0.2735 | 0.2728 | 16.495 | |
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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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