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gpt2-cl-length-sampling-3
This model is a fine-tuned version of gpt2 on the generator dataset. It achieves the following results on the evaluation set:
- Loss: 5.0773
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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 1000
- num_epochs: 1
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 6.5331 | 0.04 | 500 | 5.9440 |
| 5.252 | 0.08 | 1000 | 5.5557 |
| 4.9523 | 0.13 | 1500 | 5.3662 |
| 4.7542 | 0.17 | 2000 | 5.2549 |
| 4.6126 | 0.21 | 2500 | 5.1817 |
| 4.5013 | 0.25 | 3000 | 5.1317 |
| 4.3981 | 0.3 | 3500 | 5.1037 |
| 4.3046 | 0.34 | 4000 | 5.0879 |
| 4.2161 | 0.38 | 4500 | 5.0611 |
| 4.1315 | 0.42 | 5000 | 5.0483 |
| 4.0506 | 0.47 | 5500 | 5.0318 |
| 3.9631 | 0.51 | 6000 | 5.0247 |
| 3.8821 | 0.55 | 6500 | 5.0143 |
| 3.8021 | 0.59 | 7000 | 5.0233 |
| 3.723 | 0.64 | 7500 | 5.0218 |
| 3.6421 | 0.68 | 8000 | 5.0249 |
| 3.5797 | 0.72 | 8500 | 5.0276 |
| 3.513 | 0.76 | 9000 | 5.0309 |
| 3.4736 | 0.8 | 9500 | 5.0316 |
| 3.4299 | 0.85 | 10000 | 5.0367 |
| 3.4015 | 0.89 | 10500 | 5.0340 |
| 3.3834 | 0.93 | 11000 | 5.0330 |
| 3.3717 | 0.97 | 11500 | 5.0333 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.11.0+cu113
- Datasets 2.13.0
- Tokenizers 0.13.3
