metadata
library_name: transformers
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: 27.4606
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: 2.5400
- Rouge1: 27.4606
- Rouge2: 7.3882
- Rougel: 21.5683
- Rougelsum: 21.5769
- Gen Len: 18.8013
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: 12
- eval_batch_size: 12
- 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 |
|---|---|---|---|---|---|---|---|---|
| 2.8393 | 1.0 | 2500 | 2.5833 | 26.7701 | 6.8545 | 20.9017 | 20.9024 | 18.8193 |
| 2.7625 | 2.0 | 5000 | 2.5494 | 27.2012 | 7.1774 | 21.2519 | 21.2529 | 18.8019 |
| 2.7673 | 3.0 | 7500 | 2.5400 | 27.4606 | 7.3882 | 21.5683 | 21.5769 | 18.8013 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.19.1