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_cleaned_bbc_news_summary_model
This model is a fine-tuned version of t5-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6223
- Rouge1: 0.2173
- Rouge2: 0.17
- Rougel: 0.2036
- Rougelsum: 0.2035
- Gen Len: 18.9708
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: 0.002
- 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: 5
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
---|---|---|---|---|---|---|---|---|
No log | 1.0 | 223 | 0.7067 | 0.2044 | 0.1531 | 0.1906 | 0.1905 | 18.982 |
No log | 2.0 | 446 | 0.6486 | 0.2144 | 0.1622 | 0.1984 | 0.1987 | 18.9775 |
0.7499 | 3.0 | 669 | 0.6229 | 0.2183 | 0.1684 | 0.2038 | 0.2038 | 18.9955 |
0.7499 | 4.0 | 892 | 0.6226 | 0.2174 | 0.1672 | 0.2023 | 0.2023 | 18.9528 |
0.476 | 5.0 | 1115 | 0.6223 | 0.2173 | 0.17 | 0.2036 | 0.2035 | 18.9708 |
Framework versions
- Transformers 4.27.4
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3