metadata
license: mit
base_model: facebook/bart-large-cnn
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: Super_legal_text_summarizer
results: []
Super_legal_text_summarizer
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: 1.8504
- Rouge1: 0.4106
- Rouge2: 0.1827
- Rougel: 0.2604
- Rougelsum: 0.2624
- Gen Len: 130.9261
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: 4
- eval_batch_size: 4
- 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 | 203 | 1.9295 | 0.4004 | 0.1792 | 0.2546 | 0.2562 | 123.1576 |
| No log | 2.0 | 406 | 1.8438 | 0.4163 | 0.1886 | 0.2607 | 0.2625 | 125.9655 |
| 1.8737 | 3.0 | 609 | 1.8503 | 0.4044 | 0.1721 | 0.2498 | 0.2512 | 132.9951 |
| 1.8737 | 4.0 | 812 | 1.8504 | 0.4106 | 0.1827 | 0.2604 | 0.2624 | 130.9261 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2