Trong-Nghia
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End of training
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README.md
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---
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license: apache-2.0
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base_model: bert-large-uncased
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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: bert-large-uncased-detect-dep-v9
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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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# bert-large-uncased-detect-dep-v9
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This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.6174
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- Accuracy: 0.708
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- F1: 0.7771
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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-06
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- train_batch_size: 12
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- eval_batch_size: 12
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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: 5
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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| 0.6322 | 1.0 | 501 | 0.5564 | 0.728 | 0.8140 |
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| 0.5787 | 2.0 | 1002 | 0.5288 | 0.756 | 0.8140 |
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| 0.5301 | 3.0 | 1503 | 0.5236 | 0.748 | 0.8053 |
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| 0.4717 | 4.0 | 2004 | 0.6008 | 0.702 | 0.7847 |
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| 0.4229 | 5.0 | 2505 | 0.6174 | 0.708 | 0.7771 |
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### Framework versions
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- Transformers 4.31.0
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- Pytorch 2.0.1+cu118
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- Datasets 2.14.0
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- Tokenizers 0.13.3
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pytorch_model.bin
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runs/Jul26_04-38-06_c2c7537744b3/events.out.tfevents.1690346324.c2c7537744b3.416.0
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