DataShield
This model is a fine-tuned version of TheBloke/Mistral-7B-Instruct-v0.2-GPTQ on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.0984
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 |
---|---|---|---|
1.6923 | 0.92 | 3 | 1.5242 |
1.6311 | 1.85 | 6 | 1.4465 |
1.535 | 2.77 | 9 | 1.3561 |
1.0871 | 4.0 | 13 | 1.2616 |
1.3893 | 4.92 | 16 | 1.2132 |
1.3384 | 5.85 | 19 | 1.1729 |
1.2877 | 6.77 | 22 | 1.1437 |
0.9564 | 8.0 | 26 | 1.1171 |
1.2534 | 8.92 | 29 | 1.1011 |
0.8827 | 9.23 | 30 | 1.0984 |
Framework versions
- PEFT 0.10.0
- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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Model tree for rnaveensrinivas/DataShield
Base model
mistralai/Mistral-7B-Instruct-v0.2
Quantized
TheBloke/Mistral-7B-Instruct-v0.2-GPTQ