|
|
--- |
|
|
library_name: transformers |
|
|
license: apache-2.0 |
|
|
base_model: t5-small |
|
|
tags: |
|
|
- summarization |
|
|
- generated_from_trainer |
|
|
metrics: |
|
|
- rouge |
|
|
model-index: |
|
|
- name: t5-small-finetuned-xsum-custom-2 |
|
|
results: [] |
|
|
--- |
|
|
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
|
|
# t5-small-finetuned-xsum-custom-2 |
|
|
|
|
|
This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on an unknown dataset. |
|
|
It achieves the following results on the evaluation set: |
|
|
- Loss: 2.3786 |
|
|
- Rouge1: 31.4362 |
|
|
- Rouge2: 9.6838 |
|
|
- Rougel: 25.2999 |
|
|
- Rougelsum: 25.2866 |
|
|
|
|
|
## 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: 4e-05 |
|
|
- train_batch_size: 4 |
|
|
- eval_batch_size: 4 |
|
|
- seed: 42 |
|
|
- optimizer: Use OptimizerNames.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: 6 |
|
|
|
|
|
### Training results |
|
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | |
|
|
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|:-------:|:---------:| |
|
|
| 2.8203 | 1.0 | 5014 | 2.4866 | 29.4445 | 8.3337 | 23.5606 | 23.5476 | |
|
|
| 2.6588 | 2.0 | 10028 | 2.4326 | 30.325 | 8.9839 | 24.2942 | 24.2757 | |
|
|
| 2.5898 | 3.0 | 15042 | 2.4066 | 30.6845 | 9.2984 | 24.7842 | 24.7798 | |
|
|
| 2.5414 | 4.0 | 20056 | 2.3909 | 31.2002 | 9.4684 | 25.0031 | 24.996 | |
|
|
| 2.5094 | 5.0 | 25070 | 2.3796 | 31.3796 | 9.6549 | 25.2979 | 25.2858 | |
|
|
| 2.4899 | 6.0 | 30084 | 2.3786 | 31.4362 | 9.6838 | 25.2999 | 25.2866 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.51.3 |
|
|
- Pytorch 2.6.0+cu124 |
|
|
- Datasets 3.5.1 |
|
|
- Tokenizers 0.21.1 |
|
|
|
