metadata
base_model: facebook/bart-large-cnn
license: mit
metrics:
- rouge
tags:
- generated_from_trainer
model-index:
- name: bartcnn_finetune_4e
results: []
bartcnn_finetune_4e
This model is a fine-tuned version of facebook/bart-large-cnn on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3295
- Rouge1: 39.7896
- Rouge2: 18.8935
- Rougel: 26.783
- Rougelsum: 35.2813
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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- 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 |
|---|---|---|---|---|---|---|---|
| 0.4269 | 1.0 | 1522 | 0.3342 | 39.3787 | 18.9684 | 26.7717 | 34.7404 |
| 0.3743 | 2.0 | 3044 | 0.3276 | 39.977 | 18.9784 | 27.1332 | 35.5149 |
| 0.34 | 3.0 | 4566 | 0.3273 | 40.274 | 19.5907 | 27.3976 | 35.7839 |
| 0.3279 | 4.0 | 6088 | 0.3295 | 39.7896 | 18.8935 | 26.783 | 35.2813 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1