model
This model is a fine-tuned version of Falconsai/text_summarization on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.2990
- Rouge1: 0.1186
- Rouge2: 0.0198
- Rougel: 0.094
- Rougelsum: 0.094
- Gen Len: 19.9958
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: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss |
Epoch |
Step |
Validation Loss |
Rouge1 |
Rouge2 |
Rougel |
Rougelsum |
Gen Len |
| 3.896 |
1.0 |
600 |
3.3871 |
0.1105 |
0.0171 |
0.0874 |
0.0874 |
20.0 |
| 3.6922 |
2.0 |
1200 |
3.3257 |
0.116 |
0.0196 |
0.0921 |
0.0921 |
20.0 |
| 3.6451 |
3.0 |
1800 |
3.3037 |
0.1189 |
0.0203 |
0.0947 |
0.0947 |
19.9972 |
| 3.6179 |
4.0 |
2400 |
3.2990 |
0.1186 |
0.0198 |
0.094 |
0.094 |
19.9958 |
Framework versions
- PEFT 0.10.0
- Transformers 4.39.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
