pegasus-x-booksum-chapter
This model is a fine-tuned version of google/pegasus-x-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.5993
{'rouge1': 0.23378525407555606,
'rouge2': 0.0362962105694859,
'rougeL': 0.13587636708639556,
'rougeLsum': 0.13593997471043634}
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: 32
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- num_epochs: 8
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
2.8377 | 0.67 | 200 | 2.7300 |
2.7462 | 1.33 | 400 | 2.6613 |
2.7148 | 2.0 | 600 | 2.6345 |
2.6242 | 2.67 | 800 | 2.6249 |
2.5971 | 3.33 | 1000 | 2.6150 |
2.6103 | 4.0 | 1200 | 2.6092 |
2.5763 | 4.67 | 1400 | 2.6083 |
2.5737 | 5.33 | 1600 | 2.6035 |
2.6252 | 6.0 | 1800 | 2.6007 |
2.5402 | 6.67 | 2000 | 2.6004 |
2.5278 | 7.33 | 2200 | 2.6007 |
2.5173 | 8.0 | 2400 | 2.5993 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu117
- Datasets 2.13.1
- Tokenizers 0.13.3
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