out-glue-mnli
This model is a fine-tuned version of bert-base-uncased on the GLUE MNLI dataset. It achieves the following results on the evaluation set:
- Loss: 1.0659
- Accuracy: 0.8418
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: 192
- eval_batch_size: 256
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
Training results
Framework versions
- Transformers 4.34.0
- Pytorch 2.0.0
- Datasets 2.14.5
- Tokenizers 0.14.1
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Base model
google-bert/bert-base-uncasedDataset used to train Tural/out-glue-mnli
Evaluation results
- Accuracy on GLUE MNLIself-reported0.842