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: 2.6938
- Rouge1: 16.5765
- Rouge2: 2.4121
- Rougel: 15.4248
- Rougelsum: 15.4769
- 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 |
|---|---|---|---|---|---|---|---|---|
| 3.1215 | 1.0 | 584 | 2.7743 | 16.684 | 2.4322 | 15.4933 | 15.4944 | 19.0 |
| 3.0129 | 2.0 | 1168 | 2.7121 | 16.4123 | 2.4008 | 15.2938 | 15.3283 | 19.0 |
| 2.9533 | 3.0 | 1752 | 2.6938 | 16.5765 | 2.4121 | 15.4248 | 15.4769 | 19.0 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0+cu118
- Datasets 2.17.0
- Tokenizers 0.15.1