metadata
base_model: t5-small
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: t5-small-finetuned-xsum
results: []
t5-small-finetuned-xsum
This model is a fine-tuned version of t5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.7627
- Rouge1: 15.8972
- Rouge2: 2.2427
- Rougel: 14.6731
- Rougelsum: 14.6711
- Gen Len: 19.0
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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 3.6499 | 1.0 | 584 | 2.8964 | 16.0584 | 2.0451 | 14.8658 | 14.9034 | 18.9991 |
| 3.1367 | 2.0 | 1168 | 2.7902 | 15.6273 | 2.1489 | 14.4613 | 14.4403 | 18.9996 |
| 3.0402 | 3.0 | 1752 | 2.7627 | 15.8972 | 2.2427 | 14.6731 | 14.6711 | 19.0 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0+cu118
- Datasets 2.17.0
- Tokenizers 0.15.1