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timi-domain-classification-sim-cse
This model is a fine-tuned version of VoVanPhuc/sup-SimCSE-VietNamese-phobert-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2859
- Precision: 0.8959
- F1: 0.8656
- Accuracy: 0.9341
- Recall: 0.8372
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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | F1 | Accuracy | Recall |
---|---|---|---|---|---|---|---|
0.171 | 1.0 | 489 | 0.2451 | 0.7187 | 0.7936 | 0.8832 | 0.8858 |
0.0672 | 2.0 | 978 | 0.2163 | 0.8767 | 0.8509 | 0.9266 | 0.8266 |
0.0277 | 3.0 | 1467 | 0.2859 | 0.8959 | 0.8656 | 0.9341 | 0.8372 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3