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albert-large-v2-finetuned-rte
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: 0.6827
- Accuracy: 0.5487
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 | 18 | 0.6954 | 0.5271 |
| No log | 2.0 | 36 | 0.6860 | 0.5379 |
| No log | 3.0 | 54 | 0.6827 | 0.5487 |
| No log | 4.0 | 72 | 0.7179 | 0.5235 |
| No log | 5.0 | 90 | 0.7504 | 0.5379 |
Framework versions
- Transformers 4.15.0
- Pytorch 1.10.0+cu111
- Datasets 1.18.1
- Tokenizers 0.10.3
