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--- |
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base_model: meta-llama/Llama-2-13b-hf |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: radiopaedia-inst_240219-llama2_13b-240220 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# radiopaedia-inst_240219-llama2_13b-240220 |
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This model is a fine-tuned version of [meta-llama/Llama-2-13b-hf](https://huggingface.co./meta-llama/Llama-2-13b-hf) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7007 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0003 |
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- train_batch_size: 8 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 16 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 10 |
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- num_epochs: 2 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 0.8308 | 0.05 | 20 | 0.7775 | |
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| 0.767 | 0.11 | 40 | 0.7579 | |
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| 0.7219 | 0.16 | 60 | 0.7441 | |
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| 0.6127 | 0.21 | 80 | 0.7489 | |
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| 0.6799 | 0.27 | 100 | 0.7415 | |
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| 0.7201 | 0.32 | 120 | 0.7369 | |
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| 0.7045 | 0.37 | 140 | 0.7298 | |
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| 0.7259 | 0.42 | 160 | 0.7190 | |
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| 0.8055 | 0.48 | 180 | 0.7158 | |
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| 0.6834 | 0.53 | 200 | 0.7066 | |
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| 0.7885 | 0.58 | 220 | 0.7111 | |
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| 0.71 | 0.64 | 240 | 0.7003 | |
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| 0.7124 | 0.69 | 260 | 0.7008 | |
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| 0.6625 | 0.74 | 280 | 0.7052 | |
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| 0.691 | 0.8 | 300 | 0.6925 | |
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| 0.6148 | 0.85 | 320 | 0.6915 | |
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| 0.6727 | 0.9 | 340 | 0.6821 | |
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| 0.5608 | 0.96 | 360 | 0.6777 | |
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| 0.5981 | 1.01 | 380 | 0.6786 | |
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| 0.5295 | 1.06 | 400 | 0.7046 | |
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| 0.4217 | 1.12 | 420 | 0.7027 | |
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| 0.4026 | 1.17 | 440 | 0.7211 | |
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| 0.4469 | 1.22 | 460 | 0.7030 | |
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| 0.3774 | 1.27 | 480 | 0.7153 | |
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| 0.5217 | 1.33 | 500 | 0.7175 | |
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| 0.3966 | 1.38 | 520 | 0.6978 | |
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| 0.4662 | 1.43 | 540 | 0.7010 | |
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| 0.4038 | 1.49 | 560 | 0.6971 | |
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| 0.4514 | 1.54 | 580 | 0.7009 | |
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| 0.423 | 1.59 | 600 | 0.7069 | |
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| 0.3961 | 1.65 | 620 | 0.7030 | |
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| 0.3723 | 1.7 | 640 | 0.7008 | |
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| 0.3745 | 1.75 | 660 | 0.7008 | |
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| 0.4442 | 1.81 | 680 | 0.7087 | |
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| 0.4094 | 1.86 | 700 | 0.7040 | |
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| 0.3465 | 1.91 | 720 | 0.7015 | |
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| 0.3751 | 1.97 | 740 | 0.7007 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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