SocialSciencePegasusLargeModel
This model is a fine-tuned version of google/pegasus-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 5.7391
- Rouge1: 43.2515
- Rouge2: 13.5819
- Rougel: 29.2476
- Rougelsum: 39.2268
- Bertscore Precision: 76.5154
- Bertscore Recall: 81.3593
- Bertscore F1: 78.854
- Bleu: 0.1036
- Gen Len: 191.3589
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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Bertscore Precision | Bertscore Recall | Bertscore F1 | Bleu | Gen Len |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 6.1745 | 0.3943 | 300 | 5.9613 | 40.1903 | 12.4753 | 28.1708 | 36.7059 | 75.8626 | 80.8932 | 78.2884 | 0.0959 | 191.3589 |
| 5.8826 | 0.7885 | 600 | 5.7391 | 43.2515 | 13.5819 | 29.2476 | 39.2268 | 76.5154 | 81.3593 | 78.854 | 0.1036 | 191.3589 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.2.1
- Tokenizers 0.19.1
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Base model
google/pegasus-large