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--- |
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base_model: openai-community/gpt2 |
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library_name: peft |
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license: mit |
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metrics: |
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- accuracy |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: GPT2-small-QLoRA-finetuned-amazon-reviews-en-classification |
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results: [] |
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datasets: |
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- mteb/amazon_reviews_multi |
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language: |
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- en |
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widget: |
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- text: It`s an amazing product |
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- text: I hate this product |
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- text: It's ok, but a bit expensive |
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pipeline_tag: text-classification |
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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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# GPT2-small-QLoRA-finetuned-amazon-reviews-en-classification |
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This model is a fine-tuned version of [openai-community/gpt2](https://huggingface.co/openai-community/gpt2) on [mteb/amazon_reviews_multi](https://huggingface.co/datasets/mteb/amazon_reviews_multi) dataset. |
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It is the result of the post [QLoRA](https://maximofn.com/qlora/) |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8883 |
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- Accuracy: 0.615 |
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## Model description |
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This model provides classification of reviews in english |
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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: 224 |
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- eval_batch_size: 224 |
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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: cosine |
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- lr_scheduler_warmup_ratio: 0.1 |
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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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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 2.088 | 1.0 | 893 | 0.9780 | 0.5848 | |
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| 0.9588 | 2.0 | 1786 | 0.8940 | 0.6156 | |
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| 0.9147 | 3.0 | 2679 | 0.8918 | 0.6168 | |
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### Framework versions |
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- PEFT 0.12.0 |
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- Transformers 4.43.3 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
