privacygpt-1.2
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: 1.3523
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 |
---|---|---|---|
1.38 | 1.0000 | 5772 | 1.3702 |
1.3384 | 1.9999 | 11544 | 1.3626 |
1.325 | 2.9999 | 17316 | 1.3594 |
1.3157 | 4.0 | 23089 | 1.3574 |
1.3085 | 5.0000 | 28861 | 1.3557 |
1.3021 | 5.9999 | 34633 | 1.3546 |
1.2962 | 6.9999 | 40405 | 1.3538 |
1.2906 | 8.0 | 46178 | 1.3529 |
1.2858 | 9.0000 | 51950 | 1.3523 |
1.2811 | 9.9996 | 57720 | 1.3523 |
Framework versions
- PEFT 0.11.1
- Transformers 4.42.3
- Pytorch 2.3.1+cu118
- Datasets 2.20.0
- Tokenizers 0.19.1
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Model tree for mohananshu/privacygpt-1.2
Base model
mistralai/Mistral-7B-Instruct-v0.2
Quantized
TheBloke/Mistral-7B-Instruct-v0.2-GPTQ