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End of training

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  1. README.md +31 -31
  2. adapter_model.bin +1 -1
  3. training_args.bin +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-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0064
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  ## Model description
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@@ -50,36 +50,36 @@ 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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- | 0.866 | 0.13 | 40 | 0.1399 |
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- | 0.066 | 0.25 | 80 | 0.0188 |
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- | 0.0151 | 0.38 | 120 | 0.0152 |
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- | 0.0137 | 0.5 | 160 | 0.0141 |
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- | 0.0133 | 0.63 | 200 | 0.0130 |
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- | 0.0124 | 0.75 | 240 | 0.0115 |
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- | 0.009 | 0.88 | 280 | 0.0109 |
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- | 0.0105 | 1.0 | 320 | 0.0106 |
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- | 0.0069 | 1.13 | 360 | 0.0098 |
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- | 0.0069 | 1.25 | 400 | 0.0095 |
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- | 0.0074 | 1.38 | 440 | 0.0086 |
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- | 0.0069 | 1.5 | 480 | 0.0085 |
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- | 0.0057 | 1.63 | 520 | 0.0090 |
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- | 0.0065 | 1.75 | 560 | 0.0085 |
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- | 0.0069 | 1.88 | 600 | 0.0077 |
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- | 0.0053 | 2.0 | 640 | 0.0076 |
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- | 0.0037 | 2.13 | 680 | 0.0074 |
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- | 0.0036 | 2.25 | 720 | 0.0072 |
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- | 0.0034 | 2.38 | 760 | 0.0071 |
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- | 0.0038 | 2.5 | 800 | 0.0067 |
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- | 0.0032 | 2.63 | 840 | 0.0063 |
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- | 0.0029 | 2.75 | 880 | 0.0066 |
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- | 0.003 | 2.88 | 920 | 0.0060 |
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- | 0.0022 | 3.0 | 960 | 0.0060 |
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- | 0.0014 | 3.13 | 1000 | 0.0062 |
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- | 0.0012 | 3.26 | 1040 | 0.0064 |
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- | 0.0011 | 3.38 | 1080 | 0.0066 |
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- | 0.0011 | 3.51 | 1120 | 0.0065 |
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- | 0.0012 | 3.63 | 1160 | 0.0063 |
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- | 0.0014 | 3.76 | 1200 | 0.0064 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0055
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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+ | 0.8622 | 0.13 | 40 | 0.1426 |
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+ | 0.0711 | 0.25 | 80 | 0.0191 |
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+ | 0.0159 | 0.38 | 120 | 0.0151 |
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+ | 0.0128 | 0.5 | 160 | 0.0145 |
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+ | 0.014 | 0.63 | 200 | 0.0119 |
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+ | 0.0116 | 0.75 | 240 | 0.0127 |
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+ | 0.0098 | 0.88 | 280 | 0.0097 |
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+ | 0.0096 | 1.0 | 320 | 0.0091 |
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+ | 0.008 | 1.13 | 360 | 0.0103 |
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+ | 0.0069 | 1.25 | 400 | 0.0091 |
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+ | 0.0075 | 1.38 | 440 | 0.0090 |
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+ | 0.0068 | 1.5 | 480 | 0.0080 |
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+ | 0.0058 | 1.63 | 520 | 0.0078 |
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+ | 0.0065 | 1.75 | 560 | 0.0076 |
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+ | 0.0058 | 1.88 | 600 | 0.0071 |
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+ | 0.0054 | 2.0 | 640 | 0.0066 |
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+ | 0.0034 | 2.13 | 680 | 0.0068 |
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+ | 0.0043 | 2.25 | 720 | 0.0070 |
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+ | 0.0033 | 2.38 | 760 | 0.0068 |
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+ | 0.0027 | 2.5 | 800 | 0.0066 |
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+ | 0.0028 | 2.63 | 840 | 0.0066 |
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+ | 0.0032 | 2.75 | 880 | 0.0059 |
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+ | 0.0029 | 2.88 | 920 | 0.0063 |
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+ | 0.0026 | 3.0 | 960 | 0.0055 |
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+ | 0.0015 | 3.13 | 1000 | 0.0056 |
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+ | 0.0013 | 3.26 | 1040 | 0.0058 |
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+ | 0.001 | 3.38 | 1080 | 0.0057 |
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+ | 0.0013 | 3.51 | 1120 | 0.0056 |
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+ | 0.0009 | 3.63 | 1160 | 0.0055 |
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+ | 0.0012 | 3.76 | 1200 | 0.0055 |
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  ### Framework versions
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