metadata
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: t5-small-finetuned-xsum_epoch4
results: []
t5-small-finetuned-xsum_epoch4
This model is a fine-tuned version of t5-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.4245
- Rouge1: 29.5204
- Rouge2: 8.4931
- Rougel: 22.9705
- Rougelsum: 23.0872
- Gen Len: 18.8221
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: 32
- eval_batch_size: 32
- 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 |
|---|---|---|---|---|---|---|---|---|
| 2.7175 | 1.0 | 7620 | 2.4899 | 28.585 | 7.7626 | 22.1314 | 22.2424 | 18.8174 |
| 2.6605 | 2.0 | 15240 | 2.4486 | 29.2362 | 8.2481 | 22.7049 | 22.8227 | 18.8273 |
| 2.6368 | 3.0 | 22860 | 2.4303 | 29.4228 | 8.4312 | 22.8991 | 23.0192 | 18.8262 |
| 2.6284 | 4.0 | 30480 | 2.4245 | 29.5204 | 8.4931 | 22.9705 | 23.0872 | 18.8221 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1