gpt2-dp-2
This model is a fine-tuned version of gpt2 on the generator dataset. It achieves the following results on the evaluation set:
- Loss: 4.3038
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 |
---|---|---|---|
6.5574 | 0.53 | 500 | 5.4160 |
5.0689 | 1.07 | 1000 | 4.9377 |
4.6601 | 1.6 | 1500 | 4.6589 |
4.3967 | 2.14 | 2000 | 4.4999 |
4.1846 | 2.67 | 2500 | 4.3930 |
4.0257 | 3.21 | 3000 | 4.3408 |
3.8965 | 3.74 | 3500 | 4.2798 |
3.7483 | 4.27 | 4000 | 4.2719 |
3.6522 | 4.81 | 4500 | 4.2338 |
3.4715 | 5.34 | 5000 | 4.2545 |
3.4106 | 5.88 | 5500 | 4.2303 |
3.2009 | 6.41 | 6000 | 4.2659 |
3.1644 | 6.94 | 6500 | 4.2559 |
2.9753 | 7.48 | 7000 | 4.2917 |
2.9548 | 8.01 | 7500 | 4.2926 |
2.846 | 8.55 | 8000 | 4.3038 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.11.0+cu113
- Datasets 2.13.0
- Tokenizers 0.13.3
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