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: 2.4256
- Rouge1: 19.6262
- Rouge2: 3.6874
- Rougel: 17.4155
- Rougelsum: 17.5472
- 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: 10
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
---|---|---|---|---|---|---|---|---|
2.8869 | 1.0 | 584 | 2.6152 | 17.1618 | 2.621 | 15.8121 | 15.8907 | 19.0 |
2.829 | 2.0 | 1168 | 2.5615 | 17.486 | 2.799 | 15.9032 | 15.9821 | 19.0 |
2.7721 | 3.0 | 1752 | 2.5222 | 18.2742 | 3.0877 | 16.5789 | 16.6729 | 19.0 |
2.7416 | 4.0 | 2336 | 2.4921 | 18.8283 | 3.362 | 16.858 | 16.9738 | 19.0 |
2.7063 | 5.0 | 2920 | 2.4690 | 18.6113 | 3.2539 | 16.6872 | 16.7919 | 19.0 |
2.6686 | 6.0 | 3504 | 2.4528 | 19.2086 | 3.5071 | 17.1746 | 17.2843 | 19.0 |
2.652 | 7.0 | 4088 | 2.4403 | 19.3553 | 3.5814 | 17.1871 | 17.2981 | 19.0 |
2.6338 | 8.0 | 4672 | 2.4319 | 19.6779 | 3.6693 | 17.4134 | 17.529 | 19.0 |
2.6377 | 9.0 | 5256 | 2.4270 | 19.6024 | 3.6557 | 17.3604 | 17.4862 | 19.0 |
2.6281 | 10.0 | 5840 | 2.4256 | 19.6262 | 3.6874 | 17.4155 | 17.5472 | 19.0 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0+cu118
- Datasets 2.17.0
- Tokenizers 0.15.1