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--- |
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license: apache-2.0 |
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library_name: peft |
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tags: |
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- generated_from_trainer |
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base_model: TheBloke/Mistral-7B-Instruct-v0.2-GPTQ |
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model-index: |
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- name: Mistral-7B-Instruct-v0.2-GPTQ_retrained_NF_ToN_IoT_and_IoV |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# Mistral-7B-Instruct-v0.2-GPTQ_retrained_NF_ToN_IoT_and_IoV |
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This model is a fine-tuned version of [TheBloke/Mistral-7B-Instruct-v0.2-GPTQ](https://huggingface.co/TheBloke/Mistral-7B-Instruct-v0.2-GPTQ) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2868 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0002 |
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- train_batch_size: 1 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 4 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 2 |
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- num_epochs: 20 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 3.3006 | 1.0 | 6 | 2.3850 | |
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| 2.7433 | 2.0 | 12 | 2.2173 | |
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| 2.0996 | 3.0 | 18 | 2.0360 | |
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| 1.8643 | 4.0 | 24 | 1.8737 | |
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| 1.6957 | 5.0 | 30 | 1.6282 | |
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| 1.5218 | 6.0 | 36 | 1.3941 | |
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| 1.3533 | 7.0 | 42 | 1.1838 | |
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| 1.2254 | 8.0 | 48 | 0.9170 | |
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| 1.0833 | 9.0 | 54 | 0.7903 | |
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| 0.9952 | 10.0 | 60 | 0.6717 | |
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| 0.9268 | 11.0 | 66 | 0.5796 | |
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| 0.8677 | 12.0 | 72 | 0.5221 | |
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| 0.8085 | 13.0 | 78 | 0.4615 | |
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| 0.7681 | 14.0 | 84 | 0.3964 | |
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| 0.7376 | 15.0 | 90 | 0.3510 | |
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| 0.7131 | 16.0 | 96 | 0.3303 | |
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| 0.6965 | 17.0 | 102 | 0.3086 | |
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| 0.6863 | 18.0 | 108 | 0.2997 | |
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| 0.677 | 19.0 | 114 | 0.2917 | |
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| 0.6732 | 20.0 | 120 | 0.2868 | |
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### Framework versions |
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- PEFT 0.10.0 |
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- Transformers 4.40.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
