xlnet-base-mnli-finetuned
This model is a fine-tuned version of xlnet-base-cased on the glue dataset. It achieves the following results on the evaluation set:
- Loss: 0.3456
- Accuracy: 0.9119
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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.336 | 1.0 | 49087 | 0.3299 | 0.9010 |
| 0.2582 | 2.0 | 98174 | 0.3456 | 0.9119 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.12.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1