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Mistral_Sparse_refined_web_90p_2024-03-12

Text Generation
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Safetensors
sparse_mistral
Generated from Trainer
custom_code
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End of training

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  1. README.md +14 -4
  2. model-00001-of-00003.safetensors +1 -1
  3. model-00002-of-00003.safetensors +1 -1
  4. model-00003-of-00003.safetensors +1 -1
README.md CHANGED
@@ -15,7 +15,7 @@ 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-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 2.2572
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  ## Model description
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@@ -45,7 +45,7 @@ The following hyperparameters were used during training:
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  - total_eval_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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- - training_steps: 2350
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  ### Training results
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@@ -143,8 +143,18 @@ The following hyperparameters were used during training:
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  | 2.3209 | 0.36 | 2250 | 2.5238 |
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  | 2.4438 | 0.36 | 2275 | 2.5233 |
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  | 2.4092 | 0.37 | 2300 | 2.5190 |
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- | 2.3132 | 0.37 | 2325 | 2.5161 |
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- | 2.3556 | 0.38 | 2350 | 2.5233 |
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 2.2527
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  ## Model description
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  - total_eval_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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+ - training_steps: 2600
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  ### Training results
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  | 2.3209 | 0.36 | 2250 | 2.5238 |
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  | 2.4438 | 0.36 | 2275 | 2.5233 |
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  | 2.4092 | 0.37 | 2300 | 2.5190 |
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+ | 2.3106 | 0.37 | 2325 | 2.5217 |
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+ | 2.357 | 0.38 | 2350 | 2.5211 |
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+ | 2.3904 | 0.38 | 2375 | 2.5212 |
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+ | 2.3879 | 0.38 | 2400 | 2.5205 |
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+ | 2.2494 | 0.39 | 2425 | 2.5195 |
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+ | 2.2334 | 0.39 | 2450 | 2.5198 |
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+ | 2.3426 | 0.4 | 2475 | 2.5161 |
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+ | 2.4106 | 0.4 | 2500 | 2.5104 |
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+ | 2.41 | 0.4 | 2525 | 2.5169 |
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+ | 2.2716 | 0.41 | 2550 | 2.5128 |
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+ | 2.3065 | 0.41 | 2575 | 2.5133 |
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+ | 2.3745 | 0.42 | 2600 | 2.5268 |
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  ### Framework versions
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