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guten-rarity-all-2p5k-log-rarity-all-sort
This model is a fine-tuned version of gpt2 on the generator dataset. It achieves the following results on the evaluation set:
- Loss: 4.3117
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 |
---|---|---|---|
6.69 | 0.29 | 500 | 5.6272 |
5.3349 | 0.59 | 1000 | 5.1982 |
4.9818 | 0.88 | 1500 | 4.9441 |
4.7024 | 1.17 | 2000 | 4.7940 |
4.5531 | 1.47 | 2500 | 4.6766 |
4.4445 | 1.76 | 3000 | 4.5629 |
4.3064 | 2.05 | 3500 | 4.4888 |
4.12 | 2.35 | 4000 | 4.4409 |
4.0994 | 2.64 | 4500 | 4.3854 |
4.0596 | 2.93 | 5000 | 4.3289 |
3.8415 | 3.23 | 5500 | 4.3258 |
3.7949 | 3.52 | 6000 | 4.2992 |
3.7753 | 3.81 | 6500 | 4.2626 |
3.6705 | 4.11 | 7000 | 4.2631 |
3.5128 | 4.4 | 7500 | 4.2550 |
3.5022 | 4.69 | 8000 | 4.2439 |
3.4902 | 4.99 | 8500 | 4.2293 |
3.3248 | 5.28 | 9000 | 4.2426 |
3.3111 | 5.57 | 9500 | 4.2419 |
3.3138 | 5.87 | 10000 | 4.2408 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.11.0+cu113
- Datasets 2.13.0
- Tokenizers 0.13.3