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--- |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: Llama-360M |
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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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# Llama-360M |
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This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 5.3269 |
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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: 16 |
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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: 128 |
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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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- lr_scheduler_warmup_steps: 50 |
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- num_epochs: 40 |
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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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| 9.6295 | 0.57 | 1 | 9.6320 | |
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| 9.4685 | 1.71 | 3 | 9.4277 | |
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| 8.7308 | 2.86 | 5 | 8.9834 | |
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| 7.7978 | 4.0 | 7 | 8.3652 | |
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| 7.4895 | 4.57 | 8 | 8.1048 | |
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| 6.9772 | 5.71 | 10 | 7.7260 | |
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| 6.6117 | 6.86 | 12 | 7.4107 | |
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| 6.2461 | 8.0 | 14 | 7.1384 | |
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| 6.0376 | 8.57 | 15 | 6.9993 | |
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| 5.6415 | 9.71 | 17 | 6.7886 | |
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| 5.3502 | 10.86 | 19 | 6.6009 | |
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| 5.0627 | 12.0 | 21 | 6.4227 | |
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| 4.9292 | 12.57 | 22 | 6.3169 | |
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| 4.5619 | 13.71 | 24 | 6.1217 | |
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| 4.1745 | 14.86 | 26 | 5.9089 | |
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| 3.895 | 16.0 | 28 | 5.7244 | |
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| 3.7108 | 16.57 | 29 | 5.6837 | |
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| 3.4811 | 17.71 | 31 | 5.5533 | |
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| 3.3174 | 18.86 | 33 | 5.4525 | |
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| 3.0011 | 20.0 | 35 | 5.4535 | |
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| 2.8812 | 20.57 | 36 | 5.4168 | |
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| 2.6512 | 21.71 | 38 | 5.4168 | |
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| 2.3009 | 22.86 | 40 | 5.3269 | |
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### Framework versions |
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- Transformers 4.39.1 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
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