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--- |
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license: apache-2.0 |
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library_name: peft |
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tags: |
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- trl |
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- sft |
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- generated_from_trainer |
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base_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0 |
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model-index: |
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- name: tinyllama-tarot-v1 |
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results: [] |
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pipeline_tag: text2text-generation |
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widget: |
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- text: >- |
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Give me a one paragraph tarot reading if I pull the cards Nine of Cups, King |
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of Pentacles and Three of Cups. |
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datasets: |
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- barissglc/tarot |
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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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# tinyllama-tarot-v1 |
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This model is a fine-tuned version of [TinyLlama/TinyLlama-1.1B-Chat-v1.0](https://huggingface.co/TinyLlama/TinyLlama-1.1B-Chat-v1.0) . |
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## Model description |
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This model is a language model capable of making predictions based on tarot cards. |
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Trained to respond to questions related to topics such as love, career, and general life, tarot cards are the foundation of its predictions. |
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The model can make predictions based on the selected tarot cards. You can access the tarot cards from the tarot dataset. |
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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: 0.0002 |
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- train_batch_size: 4 |
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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: 32 |
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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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- training_steps: 250 |
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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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- PEFT 0.8.2 |
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- Transformers 4.37.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.17.1 |
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- Tokenizers 0.15.2 |
