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t5-small_finetuned_billsum_model_bs8_lr5e-05
This model is a fine-tuned version of t5-small on the billsum dataset. It achieves the following results on the evaluation set:
- Loss: 2.1736
- Rouge1: 0.1967
- Rouge2: 0.0984
- Rougel: 0.1675
- Rougelsum: 0.1677
- Gen Len: 19.0
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
---|---|---|---|---|---|---|---|---|
No log | 1.0 | 124 | 2.2775 | 0.1968 | 0.0943 | 0.1674 | 0.1674 | 19.0 |
No log | 2.0 | 248 | 2.2187 | 0.2001 | 0.0981 | 0.1705 | 0.1707 | 19.0 |
No log | 3.0 | 372 | 2.1969 | 0.1965 | 0.0987 | 0.1686 | 0.1687 | 19.0 |
No log | 4.0 | 496 | 2.1736 | 0.1967 | 0.0984 | 0.1675 | 0.1677 | 19.0 |
Framework versions
- Transformers 4.27.4
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3