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: 2.9991
- Rouge1: 0.4046
- Rouge2: 0.1585
- Rougel: 0.2567
- Rougelsum: 0.2569
- Gen Len: 94.9263
- Bert F1: 0.8757
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: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | Bert F1 |
|---|---|---|---|---|---|---|---|---|---|
| 3.5483 | 1.0 | 95 | 3.1402 | 0.409 | 0.1649 | 0.2588 | 0.2594 | 97.2947 | 0.8751 |
| 3.1867 | 2.0 | 190 | 3.0364 | 0.4075 | 0.1591 | 0.2556 | 0.2558 | 97.8263 | 0.8754 |
| 3.1221 | 3.0 | 285 | 3.0062 | 0.407 | 0.1599 | 0.2569 | 0.2572 | 95.0579 | 0.8759 |
| 3.0951 | 4.0 | 380 | 2.9991 | 0.4046 | 0.1585 | 0.2567 | 0.2569 | 94.9263 | 0.8757 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.4.0
- Datasets 3.1.0
- Tokenizers 0.20.3