cleaned_ds
This model is a fine-tuned version of sshleifer/distilbart-cnn-12-6 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 4.2803
- Rouge1: 0.2705
- Rouge2: 0.0363
- Rougel: 0.1609
- Rougelsum: 0.1609
- Generated Length: 113.0
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: 16
- eval_batch_size: 16
- 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 | Generated Length |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 1 | 4.5060 | 0.2826 | 0.0384 | 0.1694 | 0.1694 | 95.0 |
| No log | 2.0 | 2 | 4.3368 | 0.2832 | 0.0333 | 0.1701 | 0.1701 | 82.0 |
| No log | 3.0 | 3 | 4.2803 | 0.2705 | 0.0363 | 0.1609 | 0.1609 | 113.0 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1
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Base model
sshleifer/distilbart-cnn-12-6