Model save
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- model.safetensors +1 -1
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_dual-ViNLI
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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_dual-ViNLI
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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: 2.5337
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- Accuracy: 0.6082
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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: 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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- lr_scheduler_warmup_ratio: 0.1
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- training_steps: 30000
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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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| 5.8126 | 15.625 | 1000 | 3.5461 | 0.4450 |
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| 2.605 | 31.25 | 2000 | 2.7789 | 0.5404 |
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| 1.5924 | 46.875 | 3000 | 2.5432 | 0.5809 |
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| 1.2233 | 62.5 | 4000 | 2.6662 | 0.5567 |
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| 0.9236 | 78.125 | 5000 | 2.4691 | 0.5927 |
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| 0.7193 | 93.75 | 6000 | 2.4053 | 0.6027 |
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| 0.6259 | 109.375 | 7000 | 2.5938 | 0.5782 |
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| 0.5082 | 125.0 | 8000 | 2.4809 | 0.6137 |
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| 0.4438 | 140.625 | 9000 | 2.7056 | 0.5819 |
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| 0.4075 | 156.25 | 10000 | 2.6501 | 0.5946 |
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| 0.3571 | 171.875 | 11000 | 2.5337 | 0.6082 |
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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 2.21.0
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- Tokenizers 0.19.1
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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-
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size 540279452
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version https://git-lfs.github.com/spec/v1
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size 540279452
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