metadata
library_name: transformers
license: apache-2.0
base_model: t5-small
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: fine_tuned_t5_small_model_sec_5_v13
results: []
fine_tuned_t5_small_model_sec_5_v13
This model is a fine-tuned version of t5-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.7774
- Rouge1: 0.4108
- Rouge2: 0.1781
- Rougel: 0.2726
- Rougelsum: 0.2718
- Gen Len: 92.0632
- Bert F1: 0.8798
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use 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: 15
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | Bert F1 |
|---|---|---|---|---|---|---|---|---|---|
| 3.3874 | 2.1053 | 200 | 2.8941 | 0.4202 | 0.1821 | 0.2711 | 0.2709 | 96.7632 | 0.8794 |
| 3.0816 | 4.2105 | 400 | 2.8326 | 0.4123 | 0.179 | 0.2691 | 0.2695 | 92.4579 | 0.88 |
| 3.0216 | 6.3158 | 600 | 2.8048 | 0.4129 | 0.1809 | 0.2722 | 0.272 | 90.7368 | 0.8804 |
| 2.9749 | 8.4211 | 800 | 2.7914 | 0.4094 | 0.1786 | 0.272 | 0.2714 | 90.1526 | 0.8804 |
| 2.9656 | 10.5263 | 1000 | 2.7815 | 0.4105 | 0.1789 | 0.2714 | 0.2709 | 91.6474 | 0.8798 |
| 2.9433 | 12.6316 | 1200 | 2.7794 | 0.4099 | 0.1771 | 0.2712 | 0.2704 | 92.2211 | 0.8797 |
| 2.9274 | 14.7368 | 1400 | 2.7774 | 0.4108 | 0.1781 | 0.2726 | 0.2718 | 92.0632 | 0.8798 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.4.0
- Datasets 3.1.0
- Tokenizers 0.20.3