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MSc_llama3_finetuned_model_secondData

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Files changed (5) hide show
  1. README.md +28 -28
  2. adapter_model.safetensors +1 -1
  3. emissions.csv +1 -1
  4. runs/Jul17_20-22-03_msc-modeltrain-pod/events.out.tfevents.1721247727.msc-modeltrain-pod.3079.0 +3 -0
  5. 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](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: 0.7622
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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: 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
@@ -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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- | 3.7647 | 1.36 | 10 | 3.3602 |
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- | 2.8 | 2.71 | 20 | 2.0480 |
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- | 1.5819 | 4.07 | 30 | 1.2852 |
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- | 1.1832 | 5.42 | 40 | 1.1025 |
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- | 1.0318 | 6.78 | 50 | 1.0150 |
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- | 0.9674 | 8.14 | 60 | 0.9718 |
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- | 0.8975 | 9.49 | 70 | 0.9348 |
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- | 0.8375 | 10.85 | 80 | 0.8912 |
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- | 0.7851 | 12.2 | 90 | 0.8685 |
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- | 0.728 | 13.56 | 100 | 0.8443 |
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- | 0.6804 | 14.92 | 110 | 0.8038 |
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- | 0.6123 | 16.27 | 120 | 0.7684 |
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- | 0.5536 | 17.63 | 130 | 0.7314 |
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- | 0.4922 | 18.98 | 140 | 0.6943 |
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- | 0.4738 | 20.34 | 150 | 0.7095 |
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- | 0.4467 | 21.69 | 160 | 0.7344 |
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- | 0.4452 | 23.05 | 170 | 0.7397 |
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- | 0.4258 | 24.41 | 180 | 0.7332 |
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- | 0.4179 | 25.76 | 190 | 0.7436 |
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- | 0.4105 | 27.12 | 200 | 0.7373 |
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- | 0.4081 | 28.47 | 210 | 0.7596 |
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- | 0.4005 | 29.83 | 220 | 0.7552 |
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- | 0.4001 | 31.19 | 230 | 0.7652 |
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- | 0.393 | 32.54 | 240 | 0.7612 |
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- | 0.4016 | 33.9 | 250 | 0.7622 |
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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: 0.7565
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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: 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
 
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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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