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--- |
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language: |
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- en |
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thumbnail: |
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tags: |
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- text generation |
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license: cc |
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datasets: |
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- quotes-500K |
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metrics: |
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- perplexity |
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--- |
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# Quotes Generator |
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## Model description |
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This is a GPT2 model fine-tuned on the Quotes-500K dataset. |
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## Intended uses & limitations |
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For a given user prompt, it can generate motivational quotes starting with it. |
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#### How to use |
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```python |
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from transformers import AutoTokenizer, AutoModelWithLMHead |
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tokenizer = AutoTokenizer.from_pretrained("nandinib1999/quote-generator") |
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model = AutoModelWithLMHead.from_pretrained("nandinib1999/quote-generator") |
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``` |
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## Training data |
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This is the distribution of the total dataset into training, validation and test dataset for the fine-tuning task. |
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<table style="width:30%"> |
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<tr> |
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<th>train</th> |
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<td>349796</td> |
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</tr> |
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<tr> |
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<th>validation</th> |
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<td>99942</td> |
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</tr> |
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<tr> |
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<th>test</th> |
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<td>49971</td> |
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</tr> |
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</table> |
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## Training procedure |
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The model was fine-tuned using the Google Colab GPU for one epoch. The weights of the pre-trained GPT2 model were used as a base. |
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## Eval results |
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<table style="width:30%"> |
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<tr> |
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<th>Epoch</th> |
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<th>Perplexity</th> |
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</tr> |
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<tr> |
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<td>1</td> |
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<td>15.180</td> |
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</tr> |
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</table> |