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--- |
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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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metrics: |
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- rouge |
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model-index: |
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- name: t5-small-finetuned-summarizer |
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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-finetuned-summarizer |
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This model is a fine-tuned version of [google-t5/t5-small](https://huggingface.co/google-t5/t5-small) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.7567 |
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- Rouge1: 0.4206 |
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- Rouge2: 0.1916 |
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- Rougel: 0.3536 |
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- Rougelsum: 0.354 |
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- Gen Len: 16.6956 |
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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: 16 |
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- eval_batch_size: 16 |
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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: 3 |
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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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| 1.8732 | 1.0 | 921 | 1.7807 | 0.4159 | 0.1892 | 0.3488 | 0.349 | 16.6638 | |
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| 1.9217 | 2.0 | 1842 | 1.7619 | 0.4196 | 0.1908 | 0.3524 | 0.3528 | 16.7213 | |
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| 1.908 | 3.0 | 2763 | 1.7567 | 0.4206 | 0.1916 | 0.3536 | 0.354 | 16.6956 | |
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### Framework versions |
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- Transformers 4.42.4 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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