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End of training

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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](https://huggingface.co/meta-llama/Meta-Llama-3-8B) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.7565
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  ## Model description
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@@ -50,10 +50,10 @@ The following `bitsandbytes` quantization config was used during training:
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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: 32
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  - eval_batch_size: 8
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  - seed: 42
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- - gradient_accumulation_steps: 2
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  - total_train_batch_size: 64
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: cosine
@@ -64,31 +64,31 @@ 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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- | 3.7475 | 1.33 | 10 | 3.3981 |
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- | 2.804 | 2.67 | 20 | 2.0339 |
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- | 1.5726 | 4.0 | 30 | 1.2647 |
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- | 1.1893 | 5.33 | 40 | 1.1114 |
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- | 1.0463 | 6.67 | 50 | 1.0339 |
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- | 0.9701 | 8.0 | 60 | 0.9736 |
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- | 0.9065 | 9.33 | 70 | 0.9295 |
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- | 0.8548 | 10.67 | 80 | 0.9125 |
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- | 0.7974 | 12.0 | 90 | 0.8830 |
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- | 0.7462 | 13.33 | 100 | 0.8595 |
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- | 0.7056 | 14.67 | 110 | 0.8447 |
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- | 0.6521 | 16.0 | 120 | 0.8119 |
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- | 0.5957 | 17.33 | 130 | 0.7680 |
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- | 0.5399 | 18.67 | 140 | 0.7439 |
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- | 0.486 | 20.0 | 150 | 0.7158 |
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- | 0.4572 | 21.33 | 160 | 0.7180 |
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- | 0.4422 | 22.67 | 170 | 0.7232 |
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- | 0.4255 | 24.0 | 180 | 0.7245 |
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- | 0.421 | 25.33 | 190 | 0.7257 |
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- | 0.4129 | 26.67 | 200 | 0.7458 |
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- | 0.4065 | 28.0 | 210 | 0.7558 |
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- | 0.4053 | 29.33 | 220 | 0.7577 |
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- | 0.3984 | 30.67 | 230 | 0.7583 |
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- | 0.3987 | 32.0 | 240 | 0.7567 |
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- | 0.4005 | 33.33 | 250 | 0.7565 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.7284
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  ## Model description
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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
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+ - gradient_accumulation_steps: 8
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  - total_train_batch_size: 64
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: cosine
 
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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+ | 3.7573 | 1.36 | 10 | 3.3722 |
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+ | 2.8144 | 2.71 | 20 | 2.0325 |
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+ | 1.5867 | 4.07 | 30 | 1.2586 |
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+ | 1.1875 | 5.42 | 40 | 1.0898 |
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+ | 1.0487 | 6.78 | 50 | 1.0168 |
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+ | 0.9716 | 8.14 | 60 | 0.9688 |
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+ | 0.9134 | 9.49 | 70 | 0.9304 |
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+ | 0.8505 | 10.85 | 80 | 0.8940 |
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+ | 0.7963 | 12.2 | 90 | 0.8640 |
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+ | 0.7497 | 13.56 | 100 | 0.8379 |
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+ | 0.7067 | 14.92 | 110 | 0.8080 |
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+ | 0.6484 | 16.27 | 120 | 0.7751 |
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+ | 0.5945 | 17.63 | 130 | 0.7385 |
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+ | 0.5349 | 18.98 | 140 | 0.6990 |
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+ | 0.4854 | 20.34 | 150 | 0.6956 |
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+ | 0.4729 | 21.69 | 160 | 0.6990 |
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+ | 0.4496 | 23.05 | 170 | 0.6885 |
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+ | 0.4405 | 24.41 | 180 | 0.7089 |
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+ | 0.435 | 25.76 | 190 | 0.7215 |
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+ | 0.4243 | 27.12 | 200 | 0.7162 |
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+ | 0.418 | 28.47 | 210 | 0.7205 |
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+ | 0.4156 | 29.83 | 220 | 0.7296 |
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+ | 0.4153 | 31.19 | 230 | 0.7275 |
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+ | 0.4146 | 32.54 | 240 | 0.7292 |
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+ | 0.4094 | 33.9 | 250 | 0.7284 |
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  ### Framework versions
adapter_config.json CHANGED
@@ -8,7 +8,7 @@
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  "lora_alpha": 64,
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- "lora_dropout": 0.1,
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  "peft_type": "LORA",
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  "r": 32,
 
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  "layers_pattern": null,
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  "layers_to_transform": null,
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  "lora_alpha": 64,
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+ "lora_dropout": 0.2,
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  "peft_type": "LORA",
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