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--- |
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tags: |
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- generated_from_trainer |
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- not-for-all-audiences |
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model-index: |
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- name: PicoStatirik |
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results: [] |
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license: mit |
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datasets: |
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- igorktech/anekdots |
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language: |
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- ru |
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library_name: transformers |
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pipeline_tag: text-generation |
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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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# PicoStatirik |
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This model is a pre-trained version of tiny LLama2 model on an [anekdots](https://huggingface.co/datasets/igorktech/anekdots) dataset. |
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Inspired by [TinyStories](https://arxiv.org/abs/2305.07759). |
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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: 0.0005 |
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- train_batch_size: 16 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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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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- lr_scheduler_warmup_steps: 500 |
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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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### Framework versions |
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- Transformers 4.36.0.dev0 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
