| | --- |
| | license: mit |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - generator |
| | model-index: |
| | - name: gpt2-concat |
| | 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. --> |
| |
|
| | # gpt2-concat |
| |
|
| | This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the generator dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 4.3720 |
| |
|
| | ## 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: 0.0005 |
| | - train_batch_size: 64 |
| | - eval_batch_size: 64 |
| | - seed: 42 |
| | - gradient_accumulation_steps: 2 |
| | - total_train_batch_size: 128 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: cosine |
| | - lr_scheduler_warmup_steps: 1000 |
| | - num_epochs: 9 |
| | - mixed_precision_training: Native AMP |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | |
| | |:-------------:|:-----:|:----:|:---------------:| |
| | | 6.3219 | 2.31 | 500 | 5.0318 | |
| | | 4.5653 | 4.63 | 1000 | 4.4568 | |
| | | 4.3703 | 1.74 | 1500 | 4.4722 | |
| | | 4.1189 | 2.31 | 2000 | 4.3725 | |
| | | 3.9959 | 2.89 | 2500 | 4.2973 | |
| | | 3.7906 | 3.47 | 3000 | 4.2853 | |
| | | 3.7352 | 4.05 | 3500 | 4.2581 | |
| | | 3.5026 | 4.63 | 4000 | 4.2642 | |
| | | 3.4421 | 5.21 | 4500 | 4.2821 | |
| | | 3.2812 | 5.79 | 5000 | 4.2720 | |
| | | 3.1197 | 6.37 | 5500 | 4.3157 | |
| | | 3.0336 | 6.94 | 6000 | 4.3125 | |
| | | 2.8367 | 7.52 | 6500 | 4.3545 | |
| | | 2.806 | 8.1 | 7000 | 4.3663 | |
| | | 2.7076 | 8.68 | 7500 | 4.3720 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.26.1 |
| | - Pytorch 1.11.0+cu113 |
| | - Datasets 2.13.0 |
| | - Tokenizers 0.13.3 |
| |
|
