metadata
license: mit
base_model: facebook/bart-large-xsum
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: LLM_Teached_Bart
results: []
LLM_Teached_Bart
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: 1.8314
- Rouge1: 0.4852
- Rouge2: 0.2152
- Rougel: 0.3758
- Rougelsum: 0.3758
- Gen Len: 44.2945
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: 16
- 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 |
|---|---|---|---|---|---|---|---|---|
| 1.7164 | 1.0 | 625 | 1.7203 | 0.4723 | 0.209 | 0.3674 | 0.3668 | 44.1491 |
| 1.3424 | 2.0 | 1250 | 1.6998 | 0.484 | 0.2166 | 0.37 | 0.3695 | 45.3727 |
| 1.1171 | 3.0 | 1875 | 1.7546 | 0.4824 | 0.2144 | 0.3728 | 0.3728 | 43.7636 |
| 0.8193 | 4.0 | 2500 | 1.8314 | 0.4852 | 0.2152 | 0.3758 | 0.3758 | 44.2945 |
Framework versions
- Transformers 4.36.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.15.0