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--- |
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license: apache-2.0 |
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base_model: google/flan-t5-small |
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tags: |
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- generated_from_trainer |
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metrics: |
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- rouge |
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model-index: |
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- name: T5-medi |
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results: [] |
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datasets: |
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- wesley7137/qa_dataset |
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language: |
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- en |
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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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# T5-medi |
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This model is a fine-tuned version of [google/flan-t5-small](https://huggingface.co/google/flan-t5-small) on Medical QA dataset (wesley7137/qa_dataset). |
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It is just for educational purpose and does not provide accurate results. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7130 |
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- Rouge1: 0.3189 |
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- Rouge2: 0.2700 |
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- Rougel: 0.3068 |
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- Rougelsum: 0.3149 |
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## Model description |
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This is a fine-tuned T5 model for Question-Answering tasks in Medical Field |
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## Intended uses & limitations |
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May struggle with creative or subjective content. Requires fine-tuning for different tasks |
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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: 0.001 |
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- train_batch_size: 16 |
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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: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:| |
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| No log | 1.0 | 223 | 0.8782 | 0.3148 | 0.2630 | 0.3010 | 0.3098 | |
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| No log | 2.0 | 446 | 0.7820 | 0.3148 | 0.2650 | 0.3026 | 0.3111 | |
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| 1.1386 | 3.0 | 669 | 0.7456 | 0.3170 | 0.2681 | 0.3049 | 0.3131 | |
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| 1.1386 | 4.0 | 892 | 0.7259 | 0.3198 | 0.2699 | 0.3072 | 0.3156 | |
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| 0.7884 | 5.0 | 1115 | 0.7130 | 0.3189 | 0.2700 | 0.3068 | 0.3149 | |
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### Framework versions |
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- Transformers 4.39.3 |
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- Pytorch 2.1.2 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
