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: 3.9682
- Rouge1: 0.2187
- Rouge2: 0.0118
- Rougel: 0.1305
- Rougelsum: 0.1305
- Generated Length: 101.0
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 | 4.1490 | 0.2459 | 0.0132 | 0.1305 | 0.1305 | 74.5 |
| No log | 2.0 | 2 | 4.0167 | 0.2439 | 0.0121 | 0.1252 | 0.1252 | 100.0 |
| No log | 3.0 | 3 | 3.9682 | 0.2187 | 0.0118 | 0.1305 | 0.1305 | 101.0 |
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