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README.md
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---
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license: apache-2.0
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base_model: distilgpt2
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tags:
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- generated_from_trainer
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model-index:
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- name: distilgpt2-finetuned-python_code_instructions_18k_alpaca
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results: []
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datasets:
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- iamtarun/python_code_instructions_18k_alpaca
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language:
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- en
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metrics:
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- accuracy
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library_name: transformers
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pipeline_tag: text-generation
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---
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[](https://hf.co/QuantFactory)
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# QuantFactory/distilgpt2-finetuned-python_code_instructions_18k_alpaca-GGUF
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This is quantized version of [Vishaltiwari2019/distilgpt2-finetuned-python_code_instructions_18k_alpaca](https://huggingface.co/Vishaltiwari2019/distilgpt2-finetuned-python_code_instructions_18k_alpaca) created using llama.cpp
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# Original Model Card
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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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# distilgpt2-finetuned-python_code_instructions_18k_alpaca
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This model is a fine-tuned version of [distilgpt2](https://huggingface.co/distilgpt2) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.5063
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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: 8
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- eval_batch_size: 8
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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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- num_epochs: 3
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:-----:|:-----:|:---------------:|
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| 1.7264 | 1.0 | 3861 | 1.5890 |
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| 1.6046 | 2.0 | 7722 | 1.5214 |
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| 1.5359 | 3.0 | 11583 | 1.5063 |
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### Framework versions
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- Transformers 4.39.3
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- Pytorch 2.2.1+cu121
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- Datasets 2.18.0
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- Tokenizers 0.15.2
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