metadata
license: mit
base_model: facebook/bart-large-cnn
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: PTS-Bart-Large-CNN
results: []
pipeline_tag: summarization
PTS-Bart-Large-CNN
This model is a fine-tuned version of facebook/bart-large-cnn on the PTS dataset. It achieves the following results on the evaluation set:
- Loss: 1.0177
- Rouge1: 0.6339
- Rouge2: 0.4113
- Rougel: 0.5344
- Rougelsum: 0.5338
- Gen Len: 76.1278
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: 8
- eval_batch_size: 8
- 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 |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 180 | 0.9026 | 0.6109 | 0.3819 | 0.5098 | 0.5094 | 76.9722 |
| No log | 2.0 | 360 | 0.9012 | 0.6273 | 0.4054 | 0.5285 | 0.5284 | 76.3833 |
| 0.6717 | 3.0 | 540 | 0.9357 | 0.6312 | 0.4071 | 0.5297 | 0.5295 | 76.25 |
| 0.6717 | 4.0 | 720 | 1.0177 | 0.6339 | 0.4113 | 0.5344 | 0.5338 | 76.1278 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1