|
|
--- |
|
|
library_name: peft |
|
|
license: mit |
|
|
base_model: gpt2-medium |
|
|
tags: |
|
|
- generated_from_trainer |
|
|
datasets: |
|
|
- e2e_nlg |
|
|
metrics: |
|
|
- bleu |
|
|
model-index: |
|
|
- name: lora-gpt2-e2e-reproduce |
|
|
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. --> |
|
|
|
|
|
# lora-gpt2-e2e-reproduce |
|
|
|
|
|
This model is a fine-tuned version of [gpt2-medium](https://huggingface.co/gpt2-medium) on the e2e_nlg dataset. |
|
|
It achieves the following results on the evaluation set: |
|
|
- Loss: 2.4493 |
|
|
- Bleu: 0.3781 |
|
|
|
|
|
## 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: 0.0002 |
|
|
- train_batch_size: 8 |
|
|
- 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 |
|
|
- lr_scheduler_warmup_steps: 500 |
|
|
- num_epochs: 10 |
|
|
- mixed_precision_training: Native AMP |
|
|
- label_smoothing_factor: 0.1 |
|
|
|
|
|
### Training results |
|
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Bleu | |
|
|
|:-------------:|:------:|:-----:|:---------------:|:------:| |
|
|
| 2.9523 | 0.5706 | 3000 | 2.6028 | 0.3489 | |
|
|
| 2.6924 | 1.1411 | 6000 | 2.5544 | 0.3501 | |
|
|
| 2.6493 | 1.7117 | 9000 | 2.5217 | 0.4052 | |
|
|
| 2.6252 | 2.2822 | 12000 | 2.5048 | 0.3894 | |
|
|
| 2.6023 | 2.8528 | 15000 | 2.4957 | 0.4060 | |
|
|
| 2.5962 | 3.4234 | 18000 | 2.4863 | 0.3772 | |
|
|
| 2.5797 | 3.9939 | 21000 | 2.4812 | 0.3697 | |
|
|
| 2.5691 | 4.5645 | 24000 | 2.4746 | 0.3864 | |
|
|
| 2.5677 | 5.1350 | 27000 | 2.4708 | 0.3709 | |
|
|
| 2.553 | 5.7056 | 30000 | 2.4648 | 0.3787 | |
|
|
| 2.5567 | 6.2762 | 33000 | 2.4610 | 0.3754 | |
|
|
| 2.5469 | 6.8467 | 36000 | 2.4593 | 0.3670 | |
|
|
| 2.5422 | 7.4173 | 39000 | 2.4566 | 0.3663 | |
|
|
| 2.5376 | 7.9878 | 42000 | 2.4548 | 0.3621 | |
|
|
| 2.534 | 8.5584 | 45000 | 2.4538 | 0.3812 | |
|
|
| 2.5279 | 9.1289 | 48000 | 2.4532 | 0.3695 | |
|
|
| 2.5273 | 9.6995 | 51000 | 2.4493 | 0.3781 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- PEFT 0.14.0 |
|
|
- Transformers 4.48.3 |
|
|
- Pytorch 2.6.0+cu124 |
|
|
- Datasets 3.4.1 |
|
|
- Tokenizers 0.21.1 |
