<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->
fnet-large-finetuned-rte
This model is a fine-tuned version of google/fnet-large on the GLUE RTE dataset. It achieves the following results on the evaluation set:
- Loss: 0.7528
- Accuracy: 0.6426
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: 4
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.7105 | 1.0 | 623 | 0.6887 | 0.5740 |
| 0.6714 | 2.0 | 1246 | 0.6742 | 0.6209 |
| 0.509 | 3.0 | 1869 | 0.7528 | 0.6426 |
Framework versions
- Transformers 4.11.0.dev0
- Pytorch 1.9.0
- Datasets 1.12.1
- Tokenizers 0.10.3
