metadata
library_name: transformers
license: apache-2.0
base_model: t5-small
tags:
- generated_from_trainer
datasets:
- xsum
metrics:
- rouge
model-index:
- name: outputs-project-id2223
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: 31.3824
outputs-project-id2223
This model is a fine-tuned version of t5-small on the xsum dataset. It achieves the following results on the evaluation set:
- Gen Len: 19.7143
- Loss: 2.2606
- Rouge1: 31.3824
- Rouge2: 9.9473
- Rougel: 24.9422
- Rougelsum: 24.9453
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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Gen Len | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|---|
| 2.6596 | 1.0 | 12753 | 19.6937 | 2.4320 | 29.2361 | 8.3218 | 22.9893 | 22.9993 |
| 2.5914 | 2.0 | 25506 | 19.7058 | 2.3844 | 29.8093 | 8.7641 | 23.5074 | 23.5169 |
| 2.5171 | 4.0 | 51012 | 19.6821 | 2.3208 | 30.6455 | 9.3612 | 24.2744 | 24.2798 |
| 2.4813 | 6.0 | 76518 | 19.6813 | 2.2865 | 31.1312 | 9.7512 | 24.6686 | 24.6688 |
| 2.4517 | 7.0 | 89271 | 19.7118 | 2.2757 | 31.1544 | 9.7509 | 24.6982 | 24.7016 |
| 2.449 | 9.0 | 114777 | 19.7143 | 2.2606 | 31.3824 | 9.9473 | 24.9422 | 24.9453 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0