End of training
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README.md
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---
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license: apache-2.0
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base_model: bert-base-uncased
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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model-index:
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- name: Symptoms_to_Diagnosis_SonatafyAI_BERT_v1
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results: []
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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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# Symptoms_to_Diagnosis_SonatafyAI_BERT_v1
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4088
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- Accuracy: 0.9387
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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: 16
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- eval_batch_size: 16
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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: 10
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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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| No log | 1.0 | 54 | 2.7055 | 0.25 |
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| No log | 2.0 | 108 | 2.1468 | 0.6792 |
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| No log | 3.0 | 162 | 1.5608 | 0.8019 |
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| No log | 4.0 | 216 | 1.1596 | 0.8632 |
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| No log | 5.0 | 270 | 0.8834 | 0.8868 |
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| No log | 6.0 | 324 | 0.6775 | 0.9104 |
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| No log | 7.0 | 378 | 0.5516 | 0.9198 |
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| No log | 8.0 | 432 | 0.4632 | 0.9434 |
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| No log | 9.0 | 486 | 0.4273 | 0.9387 |
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| 1.2941 | 10.0 | 540 | 0.4088 | 0.9387 |
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### Framework versions
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- Transformers 4.38.2
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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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model.safetensors
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