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pegasus-xsum-whole_summary_chatGPT_and_tweetsum
This model is a fine-tuned version of google/pegasus-xsum on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.4139
- Rouge1: 27.4412
- Rouge2: 10.8393
- Rougel: 25.1988
- Rougelsum: 25.2193
- Gen Len: 14.3333
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: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 381 | 2.5524 | 26.025 | 9.5118 | 22.8243 | 22.8505 | 15.8095 |
| 2.9387 | 2.0 | 762 | 2.4394 | 29.4773 | 11.7365 | 27.6403 | 27.7766 | 15.4286 |
| 2.2822 | 3.0 | 1143 | 2.4139 | 27.4412 | 10.8393 | 25.1988 | 25.2193 | 14.3333 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.12.1
- Datasets 2.6.1
- Tokenizers 0.13.2
