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KQL/mistralv2_KQL_generation_3

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README.md CHANGED
@@ -20,7 +20,7 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) on the generator dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.3490
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  ## Model description
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@@ -39,27 +39,36 @@ More information needed
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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: 8
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  - eval_batch_size: 8
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- - lr_scheduler_type: constant
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- - lr_scheduler_warmup_steps: 0.03
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- - training_steps: 200
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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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- | 0.2485 | 7.14 | 200 | 0.3490 |
 
 
 
 
 
 
 
 
 
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  ### Framework versions
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- - PEFT 0.9.0
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- - Transformers 4.38.2
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- - Pytorch 2.2.1+cu121
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  - Datasets 2.18.0
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  - Tokenizers 0.15.2
 
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  This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) on the generator dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.4281
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 0.0003
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  - train_batch_size: 8
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  - eval_batch_size: 8
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  - seed: 42
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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_ratio: 0.1
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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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+ | 0.8896 | 1.0 | 17 | 0.6754 |
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+ | 0.5429 | 2.0 | 34 | 0.4964 |
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+ | 0.4271 | 3.0 | 51 | 0.4475 |
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+ | 0.386 | 4.0 | 68 | 0.4246 |
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+ | 0.3377 | 5.0 | 85 | 0.4118 |
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+ | 0.3068 | 6.0 | 102 | 0.4102 |
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+ | 0.29 | 7.0 | 119 | 0.4088 |
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+ | 0.2638 | 8.0 | 136 | 0.4112 |
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+ | 0.2424 | 9.0 | 153 | 0.4268 |
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+ | 0.2317 | 10.0 | 170 | 0.4281 |
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  ### Framework versions
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+ - PEFT 0.10.0
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+ - Transformers 4.39.3
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+ - Pytorch 2.2.2+cu121
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  - Datasets 2.18.0
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  - Tokenizers 0.15.2
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