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bert-base-multilingual-cased-mrpc-glue
This model is a fine-tuned version of bert-base-multilingual-cased on the datasetX dataset. It achieves the following results on the evaluation set:
- Loss: 0.5185
- Accuracy: 0.7426
- F1: 0.8059
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
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.604 | 1.09 | 500 | 0.5185 | 0.7426 | 0.8059 |
| 0.4834 | 2.18 | 1000 | 0.5550 | 0.7770 | 0.8544 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
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Model tree for rriverar75/bert-base-multilingual-cased-mrpc-glue
Base model
google-bert/bert-base-multilingual-casedDataset used to train rriverar75/bert-base-multilingual-cased-mrpc-glue
Evaluation results
- Accuracy on datasetXvalidation set self-reported0.743
- F1 on datasetXvalidation set self-reported0.806