BERT_AA_IMDB_Top50_WithoutOOC_082023_MultilingualBertBase
This model is a fine-tuned version of bert-base-multilingual-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.8084
- Accuracy: 0.8778
- F1: 0.8784
- Precision: 0.8805
- Recall: 0.8778
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: 12
- eval_batch_size: 12
- 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 | Precision | Recall |
---|---|---|---|---|---|---|---|
0.9482 | 1.0 | 2134 | 0.7728 | 0.8044 | 0.8053 | 0.8216 | 0.8044 |
0.5411 | 2.0 | 4268 | 0.6033 | 0.8408 | 0.8399 | 0.8484 | 0.8408 |
0.3207 | 3.0 | 6402 | 0.5670 | 0.8562 | 0.8566 | 0.8647 | 0.8562 |
0.1831 | 4.0 | 8536 | 0.6218 | 0.8611 | 0.8628 | 0.8686 | 0.8611 |
0.1056 | 5.0 | 10670 | 0.6755 | 0.8684 | 0.8695 | 0.8737 | 0.8684 |
0.0534 | 6.0 | 12804 | 0.7564 | 0.8702 | 0.8704 | 0.8734 | 0.8702 |
0.0311 | 7.0 | 14938 | 0.7718 | 0.8721 | 0.8729 | 0.8754 | 0.8721 |
0.016 | 8.0 | 17072 | 0.8052 | 0.8739 | 0.8750 | 0.8782 | 0.8739 |
0.0058 | 9.0 | 19206 | 0.8078 | 0.8772 | 0.8781 | 0.8806 | 0.8772 |
0.0057 | 10.0 | 21340 | 0.8084 | 0.8778 | 0.8784 | 0.8805 | 0.8778 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.8.0
- Datasets 2.10.1
- Tokenizers 0.13.2
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