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sparse_mistral_7b_refined_web_50p_2024-04-13

Text Generation
Transformers
Safetensors
sparse_llama
Generated from Trainer
custom_code
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vxbrandon commited on
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End of training

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  1. README.md +16 -6
  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: 2.1995
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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: 16
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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: 2100
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  ### Training results
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@@ -131,10 +131,20 @@ The following hyperparameters were used during training:
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  | 2.2426 | 0.62 | 1950 | 2.2463 |
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  | 2.2312 | 0.63 | 1975 | 2.2465 |
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  | 2.2679 | 0.64 | 2000 | 2.2464 |
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- | 2.1927 | 0.65 | 2025 | 2.2454 |
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- | 2.209 | 0.66 | 2050 | 2.2475 |
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- | 2.1811 | 0.66 | 2075 | 2.2444 |
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- | 2.2521 | 0.67 | 2100 | 2.2461 |
 
 
 
 
 
 
 
 
 
 
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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: 2.1985
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  ## Model description
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  - total_eval_batch_size: 16
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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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  | 2.2426 | 0.62 | 1950 | 2.2463 |
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  | 2.2312 | 0.63 | 1975 | 2.2465 |
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  | 2.2679 | 0.64 | 2000 | 2.2464 |
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+ | 2.1928 | 0.65 | 2025 | 2.2463 |
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+ | 2.2087 | 0.66 | 2050 | 2.2455 |
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+ | 2.1792 | 0.66 | 2075 | 2.2470 |
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+ | 2.252 | 0.67 | 2100 | 2.2468 |
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+ | 2.2018 | 0.68 | 2125 | 2.2456 |
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+ | 2.2006 | 0.69 | 2150 | 2.2451 |
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+ | 2.2076 | 0.7 | 2175 | 2.2449 |
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+ | 2.2436 | 0.7 | 2200 | 2.2460 |
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+ | 2.2156 | 0.71 | 2225 | 2.2477 |
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+ | 2.1348 | 0.72 | 2250 | 2.2455 |
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+ | 2.1338 | 0.73 | 2275 | 2.2450 |
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+ | 2.2147 | 0.74 | 2300 | 2.2455 |
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+ | 2.2766 | 0.74 | 2325 | 2.2444 |
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+ | 2.204 | 0.75 | 2350 | 2.2458 |
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  ### Framework versions
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