metadata
library_name: transformers
license: mit
base_model: facebook/bart-large-xsum
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: Conclusion-generator
results: []
Conclusion-generator
This model is a fine-tuned version of facebook/bart-large-xsum on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.1366
- Rouge1: 0.288
- Rouge2: 0.1138
- Rougel: 0.2018
- Rougelsum: 0.2044
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
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 404 | 1.1414 | 0.2834 | 0.1158 | 0.2022 | 0.2044 |
| 1.3686 | 2.0 | 808 | 1.1263 | 0.2823 | 0.1149 | 0.2021 | 0.2042 |
| 1.0281 | 3.0 | 1212 | 1.1366 | 0.288 | 0.1138 | 0.2018 | 0.2044 |
Framework versions
- Transformers 4.51.1
- Pytorch 2.5.1+cu124
- Datasets 3.5.0
- Tokenizers 0.21.0