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: 2.8056
- Rouge1: 16.8725
- Rouge2: 2.4419
- Rougel: 15.739
- Rougelsum: 15.7732
- 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 |
|---|---|---|---|---|---|---|---|---|
| 3.69 | 1.0 | 584 | 2.9680 | 16.6251 | 2.1336 | 15.551 | 15.606 | 18.9812 |
| 3.2113 | 2.0 | 1168 | 2.8383 | 17.0265 | 2.4793 | 15.8903 | 15.9416 | 19.0 |
| 3.0921 | 3.0 | 1752 | 2.8056 | 16.8725 | 2.4419 | 15.739 | 15.7732 | 19.0 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0+cu118
- Datasets 2.17.0
- Tokenizers 0.15.1