shawgpt-ft
This model is a fine-tuned version of TheBloke/Mistral-7B-Instruct-v0.2-GPTQ on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.9766
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 |
---|---|---|---|
2.2479 | 0.9756 | 30 | 2.0100 |
1.9424 | 1.9837 | 61 | 1.9330 |
1.891 | 2.9919 | 92 | 1.9181 |
1.8501 | 4.0 | 123 | 1.9183 |
1.8717 | 4.9756 | 153 | 1.9268 |
1.7747 | 5.9837 | 184 | 1.9379 |
1.7421 | 6.9919 | 215 | 1.9501 |
1.7147 | 8.0 | 246 | 1.9593 |
1.7473 | 8.9756 | 276 | 1.9746 |
1.6511 | 9.7561 | 300 | 1.9766 |
Framework versions
- PEFT 0.11.1
- Transformers 4.41.2
- Pytorch 2.1.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
- Downloads last month
- 0
Model tree for mb2468/shawgpt-ft
Base model
mistralai/Mistral-7B-Instruct-v0.2
Quantized
TheBloke/Mistral-7B-Instruct-v0.2-GPTQ