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all-base-rarity-all-children-rarity-all-iorder-est-5p5k-mostf
This model is a fine-tuned version of gpt2 on the generator dataset. It achieves the following results on the evaluation set:
- Loss: 4.3326
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 |
|---|---|---|---|
| 6.7525 | 0.31 | 500 | 5.6457 |
| 5.4141 | 0.63 | 1000 | 5.2112 |
| 5.0523 | 0.94 | 1500 | 4.9580 |
| 4.7674 | 1.25 | 2000 | 4.8174 |
| 4.6213 | 1.56 | 2500 | 4.6915 |
| 4.5132 | 1.88 | 3000 | 4.5796 |
| 4.3109 | 2.19 | 3500 | 4.5205 |
| 4.2115 | 2.5 | 4000 | 4.4590 |
| 4.1668 | 2.82 | 4500 | 4.3952 |
| 4.0277 | 3.13 | 5000 | 4.3712 |
| 3.8841 | 3.44 | 5500 | 4.3431 |
| 3.8738 | 3.75 | 6000 | 4.3064 |
| 3.7942 | 4.07 | 6500 | 4.2923 |
| 3.5972 | 4.38 | 7000 | 4.2869 |
| 3.5903 | 4.69 | 7500 | 4.2730 |
| 3.5681 | 5.01 | 8000 | 4.2585 |
| 3.3989 | 5.32 | 8500 | 4.2700 |
| 3.3939 | 5.63 | 9000 | 4.2694 |
| 3.3913 | 5.94 | 9500 | 4.2686 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.11.0+cu113
- Datasets 2.13.0
- Tokenizers 0.13.3
