Mistral-7B-Instruct-v0.2-GPTQ_retrained_NF_ToN_IoT_and_IoV
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: 0.2868
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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2
- num_epochs: 20
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
3.3006 | 1.0 | 6 | 2.3850 |
2.7433 | 2.0 | 12 | 2.2173 |
2.0996 | 3.0 | 18 | 2.0360 |
1.8643 | 4.0 | 24 | 1.8737 |
1.6957 | 5.0 | 30 | 1.6282 |
1.5218 | 6.0 | 36 | 1.3941 |
1.3533 | 7.0 | 42 | 1.1838 |
1.2254 | 8.0 | 48 | 0.9170 |
1.0833 | 9.0 | 54 | 0.7903 |
0.9952 | 10.0 | 60 | 0.6717 |
0.9268 | 11.0 | 66 | 0.5796 |
0.8677 | 12.0 | 72 | 0.5221 |
0.8085 | 13.0 | 78 | 0.4615 |
0.7681 | 14.0 | 84 | 0.3964 |
0.7376 | 15.0 | 90 | 0.3510 |
0.7131 | 16.0 | 96 | 0.3303 |
0.6965 | 17.0 | 102 | 0.3086 |
0.6863 | 18.0 | 108 | 0.2997 |
0.677 | 19.0 | 114 | 0.2917 |
0.6732 | 20.0 | 120 | 0.2868 |
Framework versions
- PEFT 0.10.0
- Transformers 4.40.2
- Pytorch 2.1.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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Model tree for rnaveensrinivas/Mistral-7B-Instruct-v0.2-GPTQ_retrained_NF_ToN_IoT_and_IoV
Base model
mistralai/Mistral-7B-Instruct-v0.2
Quantized
TheBloke/Mistral-7B-Instruct-v0.2-GPTQ