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--- |
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license: llama3 |
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base_model: meta-llama/Meta-Llama-3-8B |
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tags: |
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- generated_from_trainer |
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metrics: |
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- f1 |
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model-index: |
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- name: results |
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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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# results |
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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 an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4487 |
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- F1: 0.8063 |
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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: 2e-05 |
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- train_batch_size: 128 |
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- eval_batch_size: 64 |
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- seed: 42 |
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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: 35 |
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- num_epochs: 3 |
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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 | F1 | |
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|:-------------:|:------:|:----:|:---------------:|:------:| |
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| 0.8917 | 0.1368 | 16 | 0.9228 | 0.5606 | |
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| 0.8219 | 0.2735 | 32 | 0.7617 | 0.6112 | |
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| 0.7154 | 0.4103 | 48 | 0.6455 | 0.6687 | |
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| 0.6278 | 0.5470 | 64 | 0.5976 | 0.6955 | |
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| 0.5923 | 0.6838 | 80 | 0.5443 | 0.7327 | |
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| 0.5417 | 0.8205 | 96 | 0.5212 | 0.7479 | |
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| 0.5094 | 0.9573 | 112 | 0.5087 | 0.7586 | |
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| 0.4866 | 1.0940 | 128 | 0.4835 | 0.7719 | |
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| 0.4743 | 1.2308 | 144 | 0.5172 | 0.7609 | |
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| 0.4887 | 1.3675 | 160 | 0.4905 | 0.7718 | |
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| 0.452 | 1.5043 | 176 | 0.4706 | 0.7817 | |
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| 0.4592 | 1.6410 | 192 | 0.4658 | 0.7795 | |
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| 0.4372 | 1.7778 | 208 | 0.4726 | 0.7782 | |
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| 0.4387 | 1.9145 | 224 | 0.4769 | 0.7775 | |
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| 0.4242 | 2.0513 | 240 | 0.4526 | 0.7929 | |
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| 0.3881 | 2.1880 | 256 | 0.4541 | 0.7975 | |
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| 0.4081 | 2.3248 | 272 | 0.4524 | 0.8002 | |
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| 0.3768 | 2.4615 | 288 | 0.4609 | 0.7931 | |
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| 0.3838 | 2.5983 | 304 | 0.4511 | 0.8037 | |
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| 0.3888 | 2.7350 | 320 | 0.4483 | 0.8011 | |
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| 0.3791 | 2.8718 | 336 | 0.4487 | 0.8063 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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