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sparse_mistral_7b_refined_web_50p_2024-04-13

Text Generation
Transformers
Safetensors
sparse_llama
Generated from Trainer
custom_code
Model card Files Community
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: 2.2023
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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: 1350
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  ### Training results
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@@ -101,10 +101,20 @@ The following hyperparameters were used during training:
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  | 2.1837 | 0.38 | 1200 | 2.2507 |
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  | 2.1444 | 0.39 | 1225 | 2.2489 |
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  | 2.2464 | 0.4 | 1250 | 2.2499 |
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- | 2.1398 | 0.41 | 1275 | 2.2512 |
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- | 2.1929 | 0.42 | 1300 | 2.2502 |
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- | 2.2384 | 0.42 | 1325 | 2.2498 |
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- | 2.223 | 0.43 | 1350 | 2.2481 |
 
 
 
 
 
 
 
 
 
 
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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: 2.2015
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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: 1600
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  ### Training results
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  | 2.1837 | 0.38 | 1200 | 2.2507 |
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  | 2.1444 | 0.39 | 1225 | 2.2489 |
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  | 2.2464 | 0.4 | 1250 | 2.2499 |
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+ | 2.1388 | 0.41 | 1275 | 2.2508 |
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+ | 2.193 | 0.42 | 1300 | 2.2492 |
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+ | 2.2376 | 0.42 | 1325 | 2.2506 |
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+ | 2.2212 | 0.43 | 1350 | 2.2478 |
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+ | 2.2002 | 0.44 | 1375 | 2.2488 |
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+ | 2.2729 | 0.45 | 1400 | 2.2484 |
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+ | 2.2329 | 0.46 | 1425 | 2.2473 |
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+ | 2.1919 | 0.46 | 1450 | 2.2481 |
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+ | 2.2102 | 0.47 | 1475 | 2.2475 |
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+ | 2.1466 | 0.48 | 1500 | 2.2473 |
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+ | 2.1818 | 0.49 | 1525 | 2.2462 |
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+ | 2.2549 | 0.5 | 1550 | 2.2470 |
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+ | 2.2137 | 0.5 | 1575 | 2.2449 |
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+ | 2.2276 | 0.51 | 1600 | 2.2481 |
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  ### Framework versions
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