Trong-Nghia
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End of training
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README.md
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---
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license: mit
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base_model: xlnet-large-cased
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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: xlnet-large-cased-detect-dep-v5
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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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# xlnet-large-cased-detect-dep-v5
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This model is a fine-tuned version of [xlnet-large-cased](https://huggingface.co/xlnet-large-cased) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.5925
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- Accuracy: 0.73
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- F1: 0.7991
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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: 8
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- eval_batch_size: 8
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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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| 0.6442 | 1.0 | 751 | 0.5586 | 0.733 | 0.8150 |
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| 0.6032 | 2.0 | 1502 | 0.5649 | 0.743 | 0.8163 |
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| 0.5574 | 3.0 | 2253 | 0.5397 | 0.754 | 0.8148 |
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| 0.5368 | 4.0 | 3004 | 0.6118 | 0.727 | 0.8062 |
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| 0.5123 | 5.0 | 3755 | 0.5925 | 0.73 | 0.7991 |
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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 2.13.1
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- Tokenizers 0.13.3
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pytorch_model.bin
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runs/Jul20_08-33-43_3fde52620cac/events.out.tfevents.1689842769.3fde52620cac.657.0
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