SingPurcBERT-UCIRetail
This model is a fine-tuned version of google-bert/bert-base-multilingual-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4977
- Accuracy: 0.7858
- F1: 0.7857
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
---|---|---|---|---|---|
No log | 1.0 | 456 | 0.5088 | 0.7652 | 0.7624 |
0.5884 | 2.0 | 912 | 0.5192 | 0.7702 | 0.7693 |
0.478 | 3.0 | 1368 | 0.4977 | 0.7858 | 0.7857 |
0.4144 | 4.0 | 1824 | 0.6869 | 0.7825 | 0.7824 |
0.3745 | 5.0 | 2280 | 0.6851 | 0.7932 | 0.7928 |
0.3529 | 6.0 | 2736 | 0.8428 | 0.7735 | 0.7735 |
0.2819 | 7.0 | 3192 | 1.2367 | 0.7776 | 0.7775 |
0.2451 | 8.0 | 3648 | 1.3244 | 0.7669 | 0.7668 |
0.1924 | 9.0 | 4104 | 1.5086 | 0.7735 | 0.7735 |
0.1428 | 10.0 | 4560 | 1.4940 | 0.7776 | 0.7776 |
Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.0.0
- Datasets 2.14.5
- Tokenizers 0.14.1
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Model tree for MSParkDev/SingPurcBERT-UCIRetail
Base model
google-bert/bert-base-multilingual-cased