bart-base-finetuned-steel-news-Environment
This model is a fine-tuned version of facebook/bart-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 5.0878
- Rouge1: 33.7492
- Rouge2: 16.9181
- Rougel: 31.1710
- Rougelsum: 31.1290
- Rouge3: 5.2115
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: 3e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Rouge3 |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 23 | 13.6118 | 23.8890 | 8.6893 | 19.6100 | 19.7700 | 2.9881 |
| No log | 2.0 | 46 | 11.2290 | 23.8890 | 8.6893 | 19.6100 | 19.7700 | 2.9881 |
| No log | 3.0 | 69 | 10.0166 | 23.7559 | 8.2513 | 19.3871 | 19.4579 | 2.4654 |
| No log | 4.0 | 92 | 8.0345 | 27.0003 | 9.6629 | 24.1700 | 24.1187 | 2.0520 |
| 11.4324 | 5.0 | 115 | 4.9696 | 32.3997 | 12.4816 | 29.5265 | 29.4606 | 3.2122 |
Framework versions
- Transformers 4.52.2
- Pytorch 2.6.0+cu124
- Datasets 2.14.4
- Tokenizers 0.21.1