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xlm-roberta-base-VietNam-aug_replace_w2v
ThuyNT03/xlm-roberta-base-VietNam-aug_replace_w2v
xlm-roberta-base-VietNam-aug_replace_w2v is a text classification model from ThuyNT03. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- mit
- Model type
- xlm-roberta
- Access
- Public
- Created
- Aug 25, 2023
- Updated
- Aug 25, 2023
- SHA
- 7f1b9d03
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Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
xlm-roberta-base-VietNam-aug_replace_w2v
This model is a fine-tuned version of xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6015
- Accuracy: 0.77
- F1: 0.7690
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.9224 | 1.0 | 84 | 0.7441 | 0.58 | 0.4258 |
| 0.7113 | 2.0 | 168 | 0.5340 | 0.83 | 0.7787 |
| 0.5267 | 3.0 | 252 | 0.4806 | 0.81 | 0.7885 |
| 0.3822 | 4.0 | 336 | 0.5343 | 0.8 | 0.7938 |
| 0.3251 | 5.0 | 420 | 0.6015 | 0.77 | 0.7690 |
Framework versions
- Transformers 4.32.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
- Task
- Text Classification
- Library
- transformers
- Type
- xlm-roberta
- License
- mit
- Created
- Aug 25, 2023
- Updated
- Aug 25, 2023