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README.md
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---
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tags:
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- generated_from_trainer
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metrics:
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- precision
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- recall
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- f1
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- accuracy
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model-index:
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- name: disfluency-large
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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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# disfluency-large
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This model is a fine-tuned version of [vinai/phobert-large](https://huggingface.co/vinai/phobert-large) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0438
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- Precision: 0.9698
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- Recall: 0.9663
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- F1: 0.9681
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- Accuracy: 0.9921
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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: 5e-05
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- train_batch_size: 32
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- eval_batch_size: 32
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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: 15
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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| No log | 1.0 | 140 | 0.0422 | 0.9651 | 0.9627 | 0.9639 | 0.9902 |
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| No log | 2.0 | 280 | 0.0315 | 0.9718 | 0.9730 | 0.9724 | 0.9923 |
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| No log | 3.0 | 420 | 0.2221 | 0.8079 | 0.7530 | 0.7795 | 0.9355 |
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| 0.024 | 4.0 | 560 | 0.0379 | 0.9693 | 0.9675 | 0.9684 | 0.9926 |
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| 0.024 | 5.0 | 700 | 0.0499 | 0.9657 | 0.9639 | 0.9648 | 0.9905 |
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| 0.024 | 6.0 | 840 | 0.0388 | 0.9688 | 0.9688 | 0.9688 | 0.9925 |
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| 0.024 | 7.0 | 980 | 0.0438 | 0.9698 | 0.9663 | 0.9681 | 0.9921 |
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### Framework versions
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- Transformers 4.27.4
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- Pytorch 2.0.0+cu118
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- Datasets 2.11.0
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- Tokenizers 0.13.3
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