metadata
license: apache-2.0
base_model: t5-small
tags:
- generated_from_trainer
datasets:
- xsum
metrics:
- rouge
model-index:
- name: t5-small-finetuned-xsum
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: xsum
type: xsum
config: default
split: validation
args: default
metrics:
- name: Rouge1
type: rouge
value: 28.451
t5-small-finetuned-xsum
This model is a fine-tuned version of t5-small on the xsum dataset. It achieves the following results on the evaluation set:
- Loss: 2.4684
- Rouge1: 28.451
- Rouge2: 7.8513
- Rougel: 22.3844
- Rougelsum: 22.3826
- Gen Len: 18.8292
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: 100
- eval_batch_size: 100
- 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 |
|---|---|---|---|---|---|---|---|---|
| 2.7635 | 1.0 | 2041 | 2.5150 | 27.6651 | 7.3702 | 21.7165 | 21.7178 | 18.8121 |
| 2.7114 | 2.0 | 4082 | 2.4780 | 28.3617 | 7.7832 | 22.3142 | 22.3121 | 18.8227 |
| 2.695 | 3.0 | 6123 | 2.4684 | 28.451 | 7.8513 | 22.3844 | 22.3826 | 18.8292 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.1.0+cu118
- Datasets 2.20.0
- Tokenizers 0.19.1