metadata
license: mit
base_model: facebook/bart-large-cnn
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: bart-large-cnn-finetuned-laws_articles
results: []
bart-large-cnn-finetuned-laws_articles
This model is a fine-tuned version of facebook/bart-large-cnn on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.2619
- Rouge1: 37.4577
- Rouge2: 17.4395
- Rougel: 27.6576
- Rougelsum: 29.1109
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: 8
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 100
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 86 | 1.9613 | 40.6402 | 20.5834 | 31.9641 | 33.0747 |
| No log | 1.99 | 172 | 2.0573 | 39.7679 | 19.7934 | 29.9615 | 31.2392 |
| No log | 3.0 | 259 | 2.1328 | 38.2225 | 18.195 | 28.8951 | 30.4138 |
| No log | 3.99 | 345 | 2.2619 | 37.4577 | 17.4395 | 27.6576 | 29.1109 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.7
- Tokenizers 0.14.1