metadata
license: mit
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: my_text_sum_model
results: []
my_text_sum_model
This model is a fine-tuned version of facebook/bart-large-cnn on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.3750
- Rouge1: 0.3111
- Rouge2: 0.1149
- Rougel: 0.2256
- Rougelsum: 0.2256
- Gen Len: 65.5641
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 |
|---|---|---|---|---|---|---|---|---|
| 1.8443 | 1.0 | 1280 | 1.8708 | 0.3152 | 0.1199 | 0.2279 | 0.2279 | 63.8984 |
| 1.244 | 2.0 | 2560 | 1.9406 | 0.3174 | 0.1199 | 0.2303 | 0.2305 | 63.8938 |
| 0.8394 | 3.0 | 3840 | 2.1484 | 0.3118 | 0.1167 | 0.2253 | 0.2254 | 65.0891 |
| 0.5744 | 4.0 | 5120 | 2.3750 | 0.3111 | 0.1149 | 0.2256 | 0.2256 | 65.5641 |
Framework versions
- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3