ConcPurcBERT-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: 0.4789
- Accuracy: 0.7908
- F1: 0.7879
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 | 0.4790 | 0.7842 | 0.7827 |
0.5692 | 2.0 | 912 | 0.4789 | 0.7908 | 0.7879 |
0.4642 | 3.0 | 1368 | 0.5199 | 0.7718 | 0.7718 |
0.411 | 4.0 | 1824 | 0.6791 | 0.7891 | 0.7891 |
0.3674 | 5.0 | 2280 | 0.7877 | 0.7924 | 0.7924 |
0.341 | 6.0 | 2736 | 0.7359 | 0.7776 | 0.7776 |
0.2834 | 7.0 | 3192 | 1.0239 | 0.8072 | 0.8064 |
0.2405 | 8.0 | 3648 | 1.1167 | 0.7842 | 0.7842 |
0.1976 | 9.0 | 4104 | 1.3224 | 0.8048 | 0.8046 |
0.1514 | 10.0 | 4560 | 1.3551 | 0.7957 | 0.7957 |
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/ConcPurcBERT-UCIRetail
Base model
google-bert/bert-base-multilingual-cased