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shawgpt-ft

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dcrowleymunster/dcrowleymunstergpt-ft

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  1. README.md +15 -15
  2. adapter_model.safetensors +1 -1
  3. runs/Oct01_10-56-04_c475286abc1f/events.out.tfevents.1727780175.c475286abc1f.7497.0 +3 -0
  4. training_args.bin +2 -2
README.md CHANGED
@@ -16,7 +16,7 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [TheBloke/Mistral-7B-Instruct-v0.2-GPTQ](https://huggingface.co/TheBloke/Mistral-7B-Instruct-v0.2-GPTQ) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.9418
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  ## Model description
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@@ -51,22 +51,22 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:------:|:----:|:---------------:|
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- | 4.5943 | 0.9231 | 3 | 3.9645 |
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- | 4.0505 | 1.8462 | 6 | 3.4399 |
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- | 3.4816 | 2.7692 | 9 | 2.9952 |
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- | 2.2698 | 4.0 | 13 | 2.5698 |
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- | 2.7004 | 4.9231 | 16 | 2.3497 |
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- | 2.4206 | 5.8462 | 19 | 2.1789 |
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- | 2.221 | 6.7692 | 22 | 2.0562 |
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- | 1.5864 | 8.0 | 26 | 1.9965 |
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- | 2.0725 | 8.9231 | 29 | 1.9555 |
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- | 1.4315 | 9.2308 | 30 | 1.9418 |
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  ### Framework versions
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- - PEFT 0.11.1
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- - Transformers 4.41.2
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- - Pytorch 2.1.0+cu121
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- - Datasets 2.20.0
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  - Tokenizers 0.19.1
 
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  This model is a fine-tuned version of [TheBloke/Mistral-7B-Instruct-v0.2-GPTQ](https://huggingface.co/TheBloke/Mistral-7B-Instruct-v0.2-GPTQ) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.7230
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:------:|:----:|:---------------:|
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+ | 4.5919 | 0.9231 | 3 | 3.9628 |
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+ | 4.0419 | 1.8462 | 6 | 3.4360 |
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+ | 3.4592 | 2.7692 | 9 | 2.9751 |
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+ | 2.2436 | 4.0 | 13 | 2.5472 |
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+ | 2.65 | 4.9231 | 16 | 2.2938 |
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+ | 2.3231 | 5.8462 | 19 | 2.0950 |
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+ | 2.061 | 6.7692 | 22 | 1.9093 |
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+ | 1.4273 | 8.0 | 26 | 1.7719 |
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+ | 1.8052 | 8.9231 | 29 | 1.7280 |
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+ | 1.26 | 9.2308 | 30 | 1.7230 |
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  ### Framework versions
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+ - PEFT 0.13.0
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+ - Transformers 4.44.2
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+ - Pytorch 2.4.0+cu121
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+ - Datasets 3.0.1
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  - Tokenizers 0.19.1
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