metadata
base_model: google/pegasus-large
tags:
- generated_from_trainer
metrics:
- rouge
- bleu
model-index:
- name: SocialMainSectionsPegasusLargeModel
results: []
SocialMainSectionsPegasusLargeModel
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: 5.6492
- Rouge1: 44.7384
- Rouge2: 14.7302
- Rougel: 30.3839
- Rougelsum: 40.5448
- Bertscore Precision: 77.1616
- Bertscore Recall: 81.7496
- Bertscore F1: 79.3809
- Bleu: 0.1156
- Gen Len: 190.8850
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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 5.8481 | 0.6661 | 500 | 5.6492 | 44.7384 | 14.7302 | 30.3839 | 40.5448 | 77.1616 | 81.7496 | 79.3809 | 0.1156 | 190.8850 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1