metadata
license: apache-2.0
base_model: facebook/bart-large
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: bart-large_readme_summarization
results: []
bart-large_readme_summarization
This model is a fine-tuned version of facebook/bart-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.8286
- Rouge1: 0.5485
- Rouge2: 0.4096
- Rougel: 0.5242
- Rougelsum: 0.524
- Gen Len: 15.1271
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
- 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 |
|---|---|---|---|---|---|---|---|---|
| 2.1578 | 1.0 | 2916 | 1.9917 | 0.489 | 0.3382 | 0.4619 | 0.4618 | 15.9544 |
| 1.5841 | 2.0 | 5832 | 1.8486 | 0.5197 | 0.3778 | 0.4948 | 0.4942 | 15.0384 |
| 1.2896 | 3.0 | 8748 | 1.8169 | 0.5445 | 0.3982 | 0.5188 | 0.5192 | 13.994 |
| 1.0315 | 4.0 | 11664 | 1.8286 | 0.5485 | 0.4096 | 0.5242 | 0.524 | 15.1271 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1