bert-large-mnli
This model is a fine-tuned version of bert-large-cased on the GLUE MNLI dataset. It achieves the following results on the evaluation set:
- Loss: 0.9132
- Accuracy: 0.8614
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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5.0
Training results
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu117
- Datasets 2.18.0
- Tokenizers 0.13.3
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Model tree for Cheng98/bert-large-mnli
Base model
google-bert/bert-large-cased