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fnet-large-finetuned-qqp
gchhablani/fnet-large-finetuned-qqp
fnet-large-finetuned-qqp 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
- Oct 9, 2021
- SHA
- 01d3c029
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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-qqp
This model is a fine-tuned version of google/fnet-large on the GLUE QQP dataset. It achieves the following results on the evaluation set:
- Loss: 0.5515
- Accuracy: 0.8943
- F1: 0.8557
- Combined Score: 0.8750
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 | F1 | Combined Score |
|---|---|---|---|---|---|---|
| 0.4574 | 1.0 | 90962 | 0.4946 | 0.8694 | 0.8297 | 0.8496 |
| 0.3387 | 2.0 | 181924 | 0.4745 | 0.8874 | 0.8437 | 0.8655 |
| 0.2029 | 3.0 | 272886 | 0.5515 | 0.8943 | 0.8557 | 0.8750 |
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
- Oct 9, 2021