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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: 2.2091
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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: 600
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  ### Training results
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@@ -71,10 +71,20 @@ The following hyperparameters were used during training:
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  | 2.186 | 0.14 | 450 | 2.2564 |
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  | 2.2689 | 0.15 | 475 | 2.2580 |
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  | 2.2472 | 0.16 | 500 | 2.2554 |
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- | 2.201 | 0.17 | 525 | 2.2538 |
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- | 2.1977 | 0.18 | 550 | 2.2557 |
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- | 2.238 | 0.18 | 575 | 2.2562 |
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- | 2.1437 | 0.19 | 600 | 2.2550 |
 
 
 
 
 
 
 
 
 
 
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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: 2.2063
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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: 850
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  ### Training results
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  | 2.186 | 0.14 | 450 | 2.2564 |
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  | 2.2689 | 0.15 | 475 | 2.2580 |
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  | 2.2472 | 0.16 | 500 | 2.2554 |
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+ | 2.2005 | 0.17 | 525 | 2.2553 |
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+ | 2.1983 | 0.18 | 550 | 2.2552 |
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+ | 2.2388 | 0.18 | 575 | 2.2547 |
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+ | 2.1443 | 0.19 | 600 | 2.2555 |
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+ | 2.2198 | 0.2 | 625 | 2.2534 |
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+ | 2.3008 | 0.21 | 650 | 2.2536 |
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+ | 2.179 | 0.22 | 675 | 2.2521 |
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+ | 2.2069 | 0.22 | 700 | 2.2531 |
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+ | 2.1819 | 0.23 | 725 | 2.2526 |
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+ | 2.1218 | 0.24 | 750 | 2.2536 |
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+ | 2.1858 | 0.25 | 775 | 2.2513 |
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+ | 2.216 | 0.26 | 800 | 2.2519 |
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+ | 2.2266 | 0.26 | 825 | 2.2520 |
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+ | 2.1671 | 0.27 | 850 | 2.2526 |
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  ### Framework versions
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