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Christine789/QLoRA32

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README.md CHANGED
@@ -16,7 +16,7 @@ should probably proofread and complete it, then remove this comment. -->
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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: 1.7356
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  ## Model description
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@@ -44,23 +44,32 @@ The following hyperparameters were used during training:
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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: 10
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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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- | 4.5915 | 0.9231 | 3 | 3.9621 |
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- | 4.04 | 1.8462 | 6 | 3.4349 |
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- | 3.4599 | 2.7692 | 9 | 2.9746 |
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- | 2.2493 | 4.0 | 13 | 2.5418 |
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- | 2.6545 | 4.9231 | 16 | 2.2966 |
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- | 2.3332 | 5.8462 | 19 | 2.0944 |
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- | 2.0967 | 6.7692 | 22 | 1.9367 |
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- | 1.4509 | 8.0 | 26 | 1.7868 |
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- | 1.8264 | 8.9231 | 29 | 1.7411 |
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- | 1.2705 | 9.2308 | 30 | 1.7356 |
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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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: 1.3256
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  ## Model description
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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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+ | 4.595 | 0.9231 | 3 | 3.9759 |
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+ | 4.0506 | 1.8462 | 6 | 3.4371 |
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+ | 3.4359 | 2.7692 | 9 | 2.9322 |
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+ | 2.1831 | 4.0 | 13 | 2.4351 |
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+ | 2.4838 | 4.9231 | 16 | 2.1189 |
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+ | 2.0545 | 5.8462 | 19 | 1.8192 |
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+ | 1.7214 | 6.7692 | 22 | 1.6274 |
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+ | 1.1606 | 8.0 | 26 | 1.4483 |
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+ | 1.4113 | 8.9231 | 29 | 1.4009 |
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+ | 1.3405 | 9.8462 | 32 | 1.3765 |
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+ | 1.3347 | 10.7692 | 35 | 1.3599 |
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+ | 0.9488 | 12.0 | 39 | 1.3411 |
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+ | 1.2643 | 12.9231 | 42 | 1.3325 |
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+ | 1.2198 | 13.8462 | 45 | 1.3287 |
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+ | 1.2212 | 14.7692 | 48 | 1.3284 |
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+ | 0.9143 | 16.0 | 52 | 1.3271 |
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+ | 1.1902 | 16.9231 | 55 | 1.3265 |
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+ | 1.173 | 17.8462 | 58 | 1.3258 |
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+ | 0.8301 | 18.4615 | 60 | 1.3256 |
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  ### Framework versions
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