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: 0.7806
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 |
---|---|---|---|
1.1706 | 0.9919 | 92 | 1.0061 |
0.9987 | 1.9946 | 185 | 0.9524 |
0.9563 | 2.9973 | 278 | 0.9146 |
0.9325 | 3.9919 | 368 | 0.8862 |
0.9031 | 4.9919 | 460 | 0.8586 |
0.8689 | 5.9946 | 553 | 0.8344 |
0.8449 | 6.9973 | 646 | 0.8135 |
0.8345 | 7.9919 | 736 | 0.7974 |
0.8167 | 8.9919 | 828 | 0.7855 |
0.7919 | 9.9838 | 920 | 0.7806 |
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 jaki-1/shawgpt-ft
Base model
mistralai/Mistral-7B-Instruct-v0.2
Quantized
TheBloke/Mistral-7B-Instruct-v0.2-GPTQ