bert-base-multilingual-cased-finetuned
This model is a fine-tuned version of bert-base-multilingual-cased on the glue dataset. It achieves the following results on the evaluation set:
- Loss: 0.5456
- Accuracy: 0.8309
- F1: 0.8792
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: 5e-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: 3.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| No log | 1.0 | 459 | 0.5439 | 0.7549 | 0.8413 |
| 0.6021 | 2.0 | 918 | 0.5474 | 0.8039 | 0.8701 |
| 0.4386 | 3.0 | 1377 | 0.5456 | 0.8309 | 0.8792 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
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Model tree for 7Xan7der7/bert-base-multilingual-cased-finetuned
Base model
google-bert/bert-base-multilingual-casedDataset used to train 7Xan7der7/bert-base-multilingual-cased-finetuned
Evaluation results
- Accuracy on gluevalidation set self-reported0.831
- F1 on gluevalidation set self-reported0.879