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fnet-large-finetuned-wnli
gchhablani/fnet-large-finetuned-wnli
fnet-large-finetuned-wnli is a text classification model from gchhablani. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- fnet
- Access
- Public
- Created
- Mar 2, 2022
- Updated
- Sep 23, 2021
- SHA
- 910ed18a
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Datasets
Model card
From the Hugging Face model README
<!-- 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-wnli
This model is a fine-tuned version of google/fnet-large on the GLUE WNLI dataset. It achieves the following results on the evaluation set:
- Loss: 0.6953
- Accuracy: 0.3803
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: 5.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.7217 | 1.0 | 159 | 0.6864 | 0.5634 |
| 0.7056 | 2.0 | 318 | 0.6869 | 0.5634 |
| 0.706 | 3.0 | 477 | 0.6875 | 0.5634 |
| 0.7032 | 4.0 | 636 | 0.6931 | 0.5634 |
| 0.7025 | 5.0 | 795 | 0.6953 | 0.3803 |
Framework versions
- Transformers 4.11.0.dev0
- Pytorch 1.9.0
- Datasets 1.12.1
- Tokenizers 0.10.3
- Task
- Text Classification
- Library
- transformers
- Type
- fnet
- License
- apache-2.0
- Languages
- en
- Created
- Mar 2, 2022
- Updated
- Sep 23, 2021