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children_bnc_rarity_all_no_cut
This model is a fine-tuned version of gpt2 on the generator dataset. It achieves the following results on the evaluation set:
- Loss: 4.3266
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: 6
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
6.7047 | 0.29 | 500 | 5.6398 |
5.3501 | 0.58 | 1000 | 5.2066 |
5.0056 | 0.88 | 1500 | 4.9588 |
4.7258 | 1.17 | 2000 | 4.8173 |
4.5734 | 1.46 | 2500 | 4.6948 |
4.4663 | 1.75 | 3000 | 4.5804 |
4.3402 | 2.05 | 3500 | 4.5071 |
4.1471 | 2.34 | 4000 | 4.4576 |
4.1137 | 2.63 | 4500 | 4.4027 |
4.0777 | 2.92 | 5000 | 4.3468 |
3.8629 | 3.22 | 5500 | 4.3449 |
3.8078 | 3.51 | 6000 | 4.3108 |
3.8044 | 3.8 | 6500 | 4.2763 |
3.7029 | 4.09 | 7000 | 4.2803 |
3.5324 | 4.39 | 7500 | 4.2741 |
3.5239 | 4.68 | 8000 | 4.2585 |
3.5091 | 4.97 | 8500 | 4.2454 |
3.3521 | 5.26 | 9000 | 4.2592 |
3.3357 | 5.56 | 9500 | 4.2584 |
3.3348 | 5.85 | 10000 | 4.2573 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.11.0+cu113
- Datasets 2.13.0
- Tokenizers 0.13.3