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bart-cnn-science-v3-e5
This model is a fine-tuned version of theojolliffe/bart-cnn-science on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.8090
- Rouge1: 54.0053
- Rouge2: 35.5018
- Rougel: 37.3204
- Rougelsum: 51.5456
- Gen Len: 142.0
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: 2e-05
- train_batch_size: 2
- eval_batch_size: 2
- 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 | 398 | 0.9935 | 51.9669 | 31.8139 | 34.4748 | 49.5311 | 141.7407 |
| 1.1747 | 2.0 | 796 | 0.8565 | 51.7344 | 31.7341 | 34.3917 | 49.2488 | 141.7222 |
| 0.7125 | 3.0 | 1194 | 0.8252 | 52.829 | 33.2332 | 35.8865 | 50.1883 | 141.5556 |
| 0.4991 | 4.0 | 1592 | 0.8222 | 53.582 | 33.4906 | 35.7232 | 50.589 | 142.0 |
| 0.4991 | 5.0 | 1990 | 0.8090 | 54.0053 | 35.5018 | 37.3204 | 51.5456 | 142.0 |
Framework versions
- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1
