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MSc_llama3_finetuned_model_secondData

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End of training

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Files changed (6) hide show
  1. README.md +27 -27
  2. adapter_config.json +3 -3
  3. adapter_model.safetensors +2 -2
  4. emissions.csv +1 -1
  5. runs/Jul25_18-18-54_msc-modeltrain-pod/events.out.tfevents.1721931538.msc-modeltrain-pod.1693.0 +3 -0
  6. training_args.bin +1 -1
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 [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.7124
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  ## Model description
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@@ -35,7 +35,7 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 5e-05
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  - train_batch_size: 8
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  - eval_batch_size: 8
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  - seed: 42
@@ -50,31 +50,31 @@ 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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- | 3.8363 | 1.36 | 10 | 3.5698 |
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- | 3.2454 | 2.71 | 20 | 2.7356 |
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- | 2.2867 | 4.07 | 30 | 1.7205 |
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- | 1.4623 | 5.42 | 40 | 1.2840 |
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- | 1.1723 | 6.78 | 50 | 1.0982 |
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- | 1.0295 | 8.14 | 60 | 0.9766 |
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- | 0.9085 | 9.49 | 70 | 0.8723 |
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- | 0.784 | 10.85 | 80 | 0.7651 |
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- | 0.717 | 12.2 | 90 | 0.7394 |
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- | 0.6745 | 13.56 | 100 | 0.7235 |
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- | 0.6402 | 14.92 | 110 | 0.7157 |
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- | 0.6251 | 16.27 | 120 | 0.7089 |
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- | 0.5961 | 17.63 | 130 | 0.7100 |
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- | 0.5871 | 18.98 | 140 | 0.7042 |
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- | 0.5714 | 20.34 | 150 | 0.7070 |
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- | 0.5582 | 21.69 | 160 | 0.7062 |
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- | 0.5457 | 23.05 | 170 | 0.7076 |
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- | 0.5392 | 24.41 | 180 | 0.7094 |
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- | 0.5354 | 25.76 | 190 | 0.7100 |
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- | 0.5278 | 27.12 | 200 | 0.7105 |
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- | 0.5275 | 28.47 | 210 | 0.7110 |
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- | 0.5249 | 29.83 | 220 | 0.7123 |
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- | 0.5204 | 31.19 | 230 | 0.7123 |
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- | 0.5198 | 32.54 | 240 | 0.7123 |
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- | 0.5195 | 33.9 | 250 | 0.7124 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.4797
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 0.0001
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  - train_batch_size: 8
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  - eval_batch_size: 8
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  - seed: 42
 
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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+ | 3.365 | 1.36 | 10 | 2.0638 |
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+ | 1.3671 | 2.71 | 20 | 0.9814 |
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+ | 0.817 | 4.07 | 30 | 0.7618 |
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+ | 0.6648 | 5.42 | 40 | 0.7134 |
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+ | 0.5897 | 6.78 | 50 | 0.6871 |
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+ | 0.5076 | 8.14 | 60 | 0.6776 |
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+ | 0.4545 | 9.49 | 70 | 0.7360 |
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+ | 0.4059 | 10.85 | 80 | 0.7673 |
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+ | 0.3544 | 12.2 | 90 | 0.8158 |
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+ | 0.3161 | 13.56 | 100 | 0.8801 |
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+ | 0.2844 | 14.92 | 110 | 0.9591 |
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+ | 0.259 | 16.27 | 120 | 0.9817 |
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+ | 0.2405 | 17.63 | 130 | 1.0922 |
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+ | 0.2298 | 18.98 | 140 | 1.1705 |
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+ | 0.2125 | 20.34 | 150 | 1.1817 |
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+ | 0.2073 | 21.69 | 160 | 1.2862 |
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+ | 0.1998 | 23.05 | 170 | 1.3352 |
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+ | 0.1912 | 24.41 | 180 | 1.3434 |
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+ | 0.1883 | 25.76 | 190 | 1.4113 |
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+ | 0.1851 | 27.12 | 200 | 1.4113 |
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+ | 0.1796 | 28.47 | 210 | 1.4654 |
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+ | 0.1805 | 29.83 | 220 | 1.4565 |
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+ | 0.1768 | 31.19 | 230 | 1.4650 |
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+ | 0.1763 | 32.54 | 240 | 1.4769 |
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+ | 0.1752 | 33.9 | 250 | 1.4797 |
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  ### Framework versions
adapter_config.json CHANGED
@@ -7,11 +7,11 @@
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