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--- |
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library_name: transformers |
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license: llama3.2 |
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base_model: meta-llama/Llama-3.2-1B |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: llama-3.2-amharic-32k-1024-v8 |
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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-3.2-amharic-32k-1024-v8 |
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This model is a fine-tuned version of [meta-llama/Llama-3.2-1B](https://huggingface.co/meta-llama/Llama-3.2-1B) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- eval_loss: 3.9086 |
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- eval_model_preparation_time: 0.0016 |
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- eval_runtime: 16.8971 |
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- eval_samples_per_second: 619.276 |
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- eval_steps_per_second: 5.563 |
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- epoch: 13.5067 |
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- step: 130151 |
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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: 112 |
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- eval_batch_size: 112 |
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- seed: 42 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_ratio: 0.1 |
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- lr_scheduler_warmup_steps: 2000 |
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- num_epochs: 16 |
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- mixed_precision_training: Native AMP |
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### Framework versions |
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- Transformers 4.48.0 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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