|
--- |
|
license: apache-2.0 |
|
base_model: t5-small |
|
tags: |
|
- generated_from_trainer |
|
model-index: |
|
- name: setup_2C |
|
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. --> |
|
|
|
# setup_2C |
|
|
|
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: 2.0781 |
|
- Bleu1: 0.2704 |
|
- Bleu2: 0.1763 |
|
- Bleu3: 0.1219 |
|
- Bleu4: 0.087 |
|
- Meteor: 0.3266 |
|
- Bertscore Precision: 0.7963 |
|
- Bertscore Recall: 0.7572 |
|
- Bertscore F1: 0.7756 |
|
- Gen Len: 16.9447 |
|
|
|
## 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: 3 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Bleu1 | Bleu2 | Bleu3 | Bleu4 | Meteor | Bertscore Precision | Bertscore Recall | Bertscore F1 | Gen Len | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:------:|:------:|:-------------------:|:----------------:|:------------:|:-------:| |
|
| 2.3795 | 1.0 | 3125 | 2.1232 | 0.2656 | 0.1704 | 0.1161 | 0.082 | 0.3158 | 0.7927 | 0.7541 | 0.7723 | 16.9152 | |
|
| 2.2942 | 2.0 | 6250 | 2.0867 | 0.2707 | 0.1762 | 0.1214 | 0.0865 | 0.3256 | 0.7957 | 0.7568 | 0.7752 | 16.9258 | |
|
| 2.2602 | 3.0 | 9375 | 2.0781 | 0.2704 | 0.1763 | 0.1219 | 0.087 | 0.3266 | 0.7963 | 0.7572 | 0.7756 | 16.9447 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.38.2 |
|
- Pytorch 2.2.1+cu121 |
|
- Datasets 2.18.0 |
|
- Tokenizers 0.15.2 |
|
|
