shawgpt-ft
This model is a fine-tuned version of ai-forever/mGPT on the None dataset. It achieves the following results on the evaluation set:
- Loss: 3.2763
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: 0.0002
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 5.2182 | 1.0 | 10 | 4.1588 |
| 4.297 | 2.0 | 20 | 3.9610 |
| 4.0452 | 3.0 | 30 | 3.5918 |
| 3.7856 | 4.0 | 40 | 3.4631 |
| 3.5564 | 5.0 | 50 | 3.3876 |
| 3.5076 | 6.0 | 60 | 3.3417 |
| 3.4227 | 7.0 | 70 | 3.3129 |
| 3.4815 | 8.0 | 80 | 3.2946 |
| 3.4417 | 9.0 | 90 | 3.2829 |
| 3.4683 | 10.0 | 100 | 3.2763 |
Framework versions
- PEFT 0.11.1
- Transformers 4.41.2
- Pytorch 2.1.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Model tree for acdl123/shawgpt-ft
Base model
ai-forever/mGPT