|
|
--- |
|
|
library_name: transformers |
|
|
license: apache-2.0 |
|
|
base_model: google-t5/t5-small |
|
|
tags: |
|
|
- generated_from_trainer |
|
|
metrics: |
|
|
- rouge |
|
|
model-index: |
|
|
- name: my_summary_model |
|
|
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. --> |
|
|
|
|
|
# my_summary_model |
|
|
|
|
|
This model is a fine-tuned version of [google-t5/t5-small](https://huggingface.co/google-t5/t5-small) on an unknown dataset. |
|
|
It achieves the following results on the evaluation set: |
|
|
- Loss: 2.7034 |
|
|
- Rouge1: 0.145 |
|
|
- Rouge2: 0.05 |
|
|
- Rougel: 0.1188 |
|
|
- Rougelsum: 0.1187 |
|
|
- Gen Len: 20.0 |
|
|
|
|
|
## 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: 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: 4 |
|
|
- mixed_precision_training: Native AMP |
|
|
|
|
|
### Training results |
|
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
|
|
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| |
|
|
| 3.4617 | 1.0 | 62 | 3.0013 | 0.1262 | 0.0332 | 0.104 | 0.104 | 20.0 | |
|
|
| 3.0289 | 2.0 | 124 | 2.7830 | 0.1375 | 0.045 | 0.112 | 0.1123 | 20.0 | |
|
|
| 2.9931 | 3.0 | 186 | 2.7208 | 0.1439 | 0.0491 | 0.1174 | 0.1171 | 20.0 | |
|
|
| 2.9153 | 4.0 | 248 | 2.7034 | 0.145 | 0.05 | 0.1188 | 0.1187 | 20.0 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.55.0 |
|
|
- Pytorch 2.6.0+cu124 |
|
|
- Datasets 4.0.0 |
|
|
- Tokenizers 0.21.4 |
|
|
|
