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cls-comment-phobert-base-v2-v2.0
vuihocrnd/cls-comment-phobert-base-v2-v2.0
cls-comment-phobert-base-v2-v2.0 is a text classification model from vuihocrnd. Use it when you need a label for a piece of text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- roberta
- Access
- Public
- Created
- Mar 11, 2024
- Updated
- Mar 12, 2024
- SHA
- c066d658
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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. -->
cls-comment-phobert-base-v2-v2.0
This model is a fine-tuned version of vinai/phobert-base-v2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4011
- Accuracy: 0.8991
- F1 Score: 0.8423
- Recall: 0.8383
- Precision: 0.8520
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: 1e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 1500
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Score | Recall | Precision |
|---|---|---|---|---|---|---|---|
| 1.4259 | 2.11 | 100 | 1.1000 | 0.6748 | 0.3033 | 0.3441 | 0.2724 |
| 0.8607 | 4.21 | 200 | 0.6240 | 0.8074 | 0.4765 | 0.4924 | 0.4627 |
| 0.5307 | 6.32 | 300 | 0.4730 | 0.8536 | 0.6024 | 0.5973 | 0.6534 |
| 0.3704 | 8.42 | 400 | 0.4261 | 0.8615 | 0.6547 | 0.6542 | 0.6680 |
| 0.2839 | 10.53 | 500 | 0.3887 | 0.8760 | 0.7141 | 0.6891 | 0.8438 |
| 0.2141 | 12.63 | 600 | 0.3706 | 0.8879 | 0.8283 | 0.8043 | 0.8608 |
| 0.166 | 14.74 | 700 | 0.3703 | 0.8958 | 0.8516 | 0.8356 | 0.8755 |
| 0.1358 | 16.84 | 800 | 0.3852 | 0.8918 | 0.8494 | 0.8419 | 0.8595 |
| 0.1131 | 18.95 | 900 | 0.3849 | 0.8918 | 0.8406 | 0.8243 | 0.8643 |
| 0.093 | 21.05 | 1000 | 0.3629 | 0.9070 | 0.8633 | 0.8436 | 0.8875 |
| 0.0807 | 23.16 | 1100 | 0.3881 | 0.8984 | 0.8442 | 0.8344 | 0.8622 |
| 0.0728 | 25.26 | 1200 | 0.3943 | 0.8945 | 0.8398 | 0.8343 | 0.8518 |
| 0.0643 | 27.37 | 1300 | 0.4023 | 0.8991 | 0.8533 | 0.8386 | 0.8767 |
| 0.0581 | 29.47 | 1400 | 0.4024 | 0.9011 | 0.8557 | 0.8447 | 0.8733 |
| 0.0546 | 31.58 | 1500 | 0.4011 | 0.8991 | 0.8423 | 0.8383 | 0.8520 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- Created
- Mar 11, 2024
- Updated
- Mar 12, 2024