metadata
license: mit
base_model: facebook/bart-large-xsum
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: reddit_summarization_model
results: []
reddit_summarization_model
This model is a fine-tuned version of facebook/bart-large-xsum on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.9410
- Rouge1: 0.4169
- Rouge2: 0.163
- Rougel: 0.276
- Rougelsum: 0.3001
- Gen Len: 61.6276
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: 3
- eval_batch_size: 3
- seed: 42
- gradient_accumulation_steps: 3
- total_train_batch_size: 9
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 1.9905 | 1.0 | 972 | 1.8412 | 0.412 | 0.1593 | 0.2725 | 0.2965 | 61.7025 |
| 1.5293 | 2.0 | 1944 | 1.8022 | 0.4162 | 0.1634 | 0.2766 | 0.2998 | 61.6673 |
| 1.2934 | 3.0 | 2916 | 1.8352 | 0.4194 | 0.1641 | 0.2789 | 0.3019 | 61.548 |
| 1.1481 | 4.0 | 3888 | 1.8898 | 0.415 | 0.1623 | 0.2753 | 0.2985 | 61.5825 |
| 1.04 | 5.0 | 4860 | 1.9410 | 0.4169 | 0.163 | 0.276 | 0.3001 | 61.6276 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0