metadata
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: []
lora-gpt2-e2e-reproduce
This model is a fine-tuned version of 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