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bart-cnn-science-v3-e4
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: 0.8265
- Rouge1: 53.0296
- Rouge2: 33.4957
- Rougel: 35.8876
- Rougelsum: 50.0786
- Gen Len: 141.5926
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: 4
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
---|---|---|---|---|---|---|---|---|
No log | 1.0 | 398 | 0.9965 | 52.4108 | 32.1506 | 35.0281 | 50.0368 | 142.0 |
1.176 | 2.0 | 796 | 0.8646 | 52.7182 | 32.9681 | 35.1454 | 49.9527 | 141.8333 |
0.7201 | 3.0 | 1194 | 0.8354 | 52.5417 | 32.6428 | 35.8703 | 49.8037 | 142.0 |
0.5244 | 4.0 | 1592 | 0.8265 | 53.0296 | 33.4957 | 35.8876 | 50.0786 | 141.5926 |
Framework versions
- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1