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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_keras_callback |
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model-index: |
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- name: suarkadipa/GPT-2-finetuned-medical-domain |
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results: [] |
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datasets: |
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- argilla/medical-domain |
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--- |
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<!-- This model card has been generated automatically according to the information Keras had access to. You should |
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probably proofread and complete it, then remove this comment. --> |
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# suarkadipa/GPT-2-finetuned-medical-domain |
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This model is a fine-tuned version of [distilgpt2](https://huggingface.co/distilgpt2) on an argilla/medical-domain dataset. Based on https://python.plainenglish.io/i-fine-tuned-gpt-2-on-100k-scientific-papers-heres-the-result-903f0784fe65 |
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It achieves the following results on the evaluation set: |
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- Train Loss: 2.5822 |
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- Validation Loss: 2.1133 |
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- Epoch: 0 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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# How to run in Google Colab |
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```python |
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from transformers import AutoTokenizer, AutoModelForCausalLM |
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tokenizer_fromhub = AutoTokenizer.from_pretrained("suarkadipa/GPT-2-finetuned-papers") |
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model_fromhub = AutoModelForCausalLM.from_pretrained("suarkadipa/GPT-2-finetuned-papers", from_tf=True) |
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text_generator = pipeline( |
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"text-generation", |
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model=model_fromhub, |
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tokenizer=tokenizer_fromhub, |
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framework="tf", |
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max_new_tokens=3000 |
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) |
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test_sentence = "the lungs" |
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res=text_generator(test_sentence)[0]["generated_text"].replace("\n", " ") |
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``` |
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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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- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'ExponentialDecay', 'config': {'initial_learning_rate': 0.0005, 'decay_steps': 500, 'decay_rate': 0.95, 'staircase': False, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01} |
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- training_precision: float32 |
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### Training results |
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| Train Loss | Validation Loss | Epoch | |
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|:----------:|:---------------:|:-----:| |
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| 2.5822 | 2.1133 | 0 | |
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### Framework versions |
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- Transformers 4.29.2 |
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- TensorFlow 2.12.0 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
