|
|
--- |
|
|
license: apache-2.0 |
|
|
base_model: t5-small |
|
|
tags: |
|
|
- generated_from_trainer |
|
|
metrics: |
|
|
- rouge |
|
|
model-index: |
|
|
- name: shadow |
|
|
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. --> |
|
|
|
|
|
# shadow |
|
|
|
|
|
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: 1.2249 |
|
|
- Rouge1: 0.2638 |
|
|
- Rouge2: 0.1186 |
|
|
- Rougel: 0.2171 |
|
|
- Rougelsum: 0.2169 |
|
|
- Gen Len: 146.8555 |
|
|
|
|
|
## 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: 8 |
|
|
- eval_batch_size: 8 |
|
|
- 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 | |
|
|
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:--------:| |
|
|
| 2.6504 | 1.0 | 718 | 1.5109 | 0.0112 | 0.0026 | 0.0098 | 0.0098 | 13.3183 | |
|
|
| 1.7193 | 2.0 | 1436 | 1.3836 | 0.1697 | 0.0487 | 0.1355 | 0.1354 | 140.8933 | |
|
|
| 1.5492 | 3.0 | 2154 | 1.3174 | 0.202 | 0.0564 | 0.1591 | 0.1592 | 153.2811 | |
|
|
| 1.51 | 4.0 | 2872 | 1.2829 | 0.2152 | 0.0691 | 0.1708 | 0.1709 | 156.3921 | |
|
|
| 1.4341 | 5.0 | 3590 | 1.2613 | 0.2336 | 0.0895 | 0.1866 | 0.1866 | 156.2713 | |
|
|
| 1.4335 | 6.0 | 4308 | 1.2466 | 0.2534 | 0.1118 | 0.2073 | 0.2075 | 146.7207 | |
|
|
| 1.4033 | 7.0 | 5026 | 1.2363 | 0.2591 | 0.1168 | 0.213 | 0.213 | 144.5354 | |
|
|
| 1.4045 | 8.0 | 5744 | 1.2298 | 0.261 | 0.1171 | 0.2149 | 0.2149 | 147.7884 | |
|
|
| 1.3839 | 9.0 | 6462 | 1.2260 | 0.263 | 0.1178 | 0.216 | 0.2159 | 147.3518 | |
|
|
| 1.3863 | 10.0 | 7180 | 1.2249 | 0.2638 | 0.1186 | 0.2171 | 0.2169 | 146.8555 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.35.2 |
|
|
- Pytorch 2.1.1+cu121 |
|
|
- Datasets 2.15.0 |
|
|
- Tokenizers 0.15.0 |
|
|
|
