metadata
base_model: google/pegasus-large
tags:
- generated_from_trainer
metrics:
- rouge
- bleu
model-index:
- name: LifeSciencePegasusLargeModel
results: []
LifeSciencePegasusLargeModel
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: 5.6523
- Rouge1: 44.7761
- Rouge2: 12.6726
- Rougel: 29.0847
- Rougelsum: 40.7566
- Bertscore Precision: 77.9283
- Bertscore Recall: 81.5854
- Bertscore F1: 79.7092
- Bleu: 0.0886
- Gen Len: 225.7220
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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 6.2586 | 0.2643 | 300 | 6.0453 | 40.1947 | 11.1082 | 26.9714 | 36.2747 | 76.6344 | 80.8385 | 78.6731 | 0.0775 | 225.7220 |
| 6.0213 | 0.5286 | 600 | 5.7899 | 43.2445 | 12.1722 | 28.4564 | 39.1524 | 77.5194 | 81.3755 | 79.3945 | 0.0856 | 225.7220 |
| 5.9018 | 0.7929 | 900 | 5.6523 | 44.7761 | 12.6726 | 29.0847 | 40.7566 | 77.9283 | 81.5854 | 79.7092 | 0.0886 | 225.7220 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.2.1
- Tokenizers 0.19.1