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albert-large-v2-finetuned-wnli
This model is a fine-tuned version of albert-large-v2 on the glue dataset. It achieves the following results on the evaluation set:
- Loss: 0.6919
- Accuracy: 0.5352
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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 17 | 0.7292 | 0.4366 |
| No log | 2.0 | 34 | 0.6919 | 0.5352 |
| No log | 3.0 | 51 | 0.7084 | 0.4648 |
| No log | 4.0 | 68 | 0.7152 | 0.5352 |
| No log | 5.0 | 85 | 0.7343 | 0.5211 |
Framework versions
- Transformers 4.15.0
- Pytorch 1.10.0+cu111
- Datasets 1.18.1
- Tokenizers 0.10.3
