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README.md
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---
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base_model: demdecuong/vihealthbert-base-word
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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: vihealthbert-w_unsup-SynPD
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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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# vihealthbert-w_unsup-SynPD
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This model is a fine-tuned version of [demdecuong/vihealthbert-base-word](https://huggingface.co/demdecuong/vihealthbert-base-word) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.5540
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- Accuracy: 0.6880
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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: 3e-05
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- train_batch_size: 32
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- eval_batch_size: 16
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- seed: 21363
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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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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 10.0
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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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| 7.0234 | 0.8616 | 5000 | 2.5909 | 0.5576 |
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| 5.2736 | 1.7232 | 10000 | 2.1890 | 0.5962 |
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| 4.9126 | 2.5849 | 15000 | 1.9095 | 0.6381 |
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| 4.791 | 3.4465 | 20000 | 1.8286 | 0.6469 |
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| 4.6538 | 4.3081 | 25000 | 1.7144 | 0.6644 |
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| 4.5846 | 5.1697 | 30000 | 1.6779 | 0.6704 |
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| 4.5568 | 6.0314 | 35000 | 1.6362 | 0.6766 |
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| 4.5079 | 6.8930 | 40000 | 1.6008 | 0.6814 |
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| 4.469 | 7.7546 | 45000 | 1.6064 | 0.6805 |
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| 4.4514 | 8.6162 | 50000 | 1.5800 | 0.6852 |
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| 4.4317 | 9.4779 | 55000 | 1.5540 | 0.6880 |
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### Framework versions
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- Transformers 4.40.2
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- Pytorch 2.0.1+cu118
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- Datasets 2.19.1
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- Tokenizers 0.19.1
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