thesis-bart-finetuned
This model is a fine-tuned version of sshleifer/distilbart-cnn-6-6 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.4528
- Rouge1: 40.6581
- Rouge2: 14.5046
- Rougel: 21.8144
- Rougelsum: 36.4842
- Gen Len: 141.4392
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: 1
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 2.5368 | 1.0 | 2811 | 2.4528 | 40.6581 | 14.5046 | 21.8144 | 36.4842 | 141.4392 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2
- Downloads last month
- 9
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.