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timi-domain-classification-sim-cse-v2
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: 0.4414
- Precision: 0.8907
- F1: 0.8483
- Accuracy: 0.9266
- Recall: 0.8097
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: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | F1 | Accuracy | Recall |
---|---|---|---|---|---|---|---|
0.1768 | 1.0 | 489 | 0.2526 | 0.7957 | 0.7932 | 0.8955 | 0.7907 |
0.0754 | 2.0 | 978 | 0.2429 | 0.8320 | 0.8398 | 0.9180 | 0.8478 |
0.0331 | 3.0 | 1467 | 0.3166 | 0.8279 | 0.8408 | 0.9180 | 0.8541 |
0.0159 | 4.0 | 1956 | 0.3733 | 0.8706 | 0.8547 | 0.9277 | 0.8393 |
0.0065 | 5.0 | 2445 | 0.4414 | 0.8907 | 0.8483 | 0.9266 | 0.8097 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu117
- Datasets 2.1.0
- Tokenizers 0.13.3