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End of training

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+ ---
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+ base_model: vinai/phobert-base
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - f1
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+ - precision
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+ - recall
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+ model-index:
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+ - name: my_model
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+ results: []
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+ ---
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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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+
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+ # my_model
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+
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+ This model is a fine-tuned version of [vinai/phobert-base](https://huggingface.co/vinai/phobert-base) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.3275
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+ - F1: 0.7678
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+ - Precision: 0.7851
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+ - Recall: 0.7512
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 2
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | F1 | Precision | Recall |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|:---------:|:------:|
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+ | 0.1919 | 1.0 | 2423 | 0.3585 | 0.7545 | 0.7644 | 0.7448 |
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+ | 0.2079 | 2.0 | 4846 | 0.3275 | 0.7678 | 0.7851 | 0.7512 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.33.0
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+ - Pytorch 2.0.0
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+ - Datasets 2.1.0
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+ - Tokenizers 0.13.3