metadata
library_name: transformers
license: apache-2.0
base_model: niteshsah-760/BART-LARGE-DIALOGSUM
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: BART-LARGE-fine_tuned
results: []
BART-LARGE-fine_tuned
This model is a fine-tuned version of niteshsah-760/BART-LARGE-DIALOGSUM on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5467
- Rouge1: 58.168
- Rouge2: 45.9825
- Rougel: 54.3562
- Rougelsum: 54.4552
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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| 0.6587 | 1.0 | 563 | 0.6037 | 56.3206 | 44.2624 | 52.832 | 52.8704 |
| 0.6162 | 2.0 | 1126 | 0.5719 | 56.8789 | 44.8139 | 53.3803 | 53.4437 |
| 0.5815 | 3.0 | 1689 | 0.5560 | 57.6576 | 45.5559 | 53.943 | 54.0187 |
| 0.5663 | 4.0 | 2252 | 0.5491 | 57.9815 | 45.9701 | 54.2183 | 54.3077 |
| 0.546 | 5.0 | 2815 | 0.5467 | 58.168 | 45.9825 | 54.3562 | 54.4552 |
Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0