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Training completed!

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README.md ADDED
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+ ---
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+ base_model: vinai/phobert-base-v2
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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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+ - f1
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+ model-index:
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+ - name: PhoBERT-Final_Mixed-train
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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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+ # PhoBERT-Final_Mixed-train
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+
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+ This model is a fine-tuned version of [vinai/phobert-base-v2](https://huggingface.co/vinai/phobert-base-v2) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.7743
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+ - Accuracy: 0.74
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+ - F1: 0.7384
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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: 8
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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+ | 1.0436 | 1.0 | 44 | 0.9281 | 0.59 | 0.5245 |
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+ | 0.7885 | 2.0 | 88 | 0.7627 | 0.65 | 0.5836 |
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+ | 0.6335 | 3.0 | 132 | 0.7060 | 0.7 | 0.6803 |
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+ | 0.5129 | 4.0 | 176 | 0.7583 | 0.69 | 0.6779 |
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+ | 0.4076 | 5.0 | 220 | 0.7353 | 0.72 | 0.7158 |
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+ | 0.3184 | 6.0 | 264 | 0.7080 | 0.73 | 0.7257 |
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+ | 0.2919 | 7.0 | 308 | 0.7543 | 0.73 | 0.7272 |
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+ | 0.2296 | 8.0 | 352 | 0.7743 | 0.74 | 0.7384 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.32.1
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+ - Pytorch 2.0.1+cu118
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+ - Datasets 2.14.4
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+ - Tokenizers 0.13.3
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+ "layer_norm_eps": 1e-05,
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+ "model_type": "roberta",
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+ "num_attention_heads": 12,
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+ "position_embedding_type": "absolute",
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+ "problem_type": "single_label_classification",
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+ "tokenizer_class": "PhobertTokenizer",
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+ "torch_dtype": "float32",
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