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---
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license: apache-2.0
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base_model: google/fnet-base
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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model-index:
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- name: FNet_Classification
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# FNet_Classification
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This model is a fine-tuned version of [google/fnet-base](https://huggingface.co/google/fnet-base) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.3889
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- Accuracy: 0.813
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 2e-05
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- train_batch_size: 16
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- eval_batch_size: 16
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 2
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 0.5529 | 1.0 | 625 | 0.4144 | 0.804 |
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| 0.4314 | 2.0 | 1250 | 0.3889 | 0.813 |
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### Framework versions
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- Transformers 4.32.1
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- Pytorch 2.2.1+cpu
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- Datasets 2.12.0
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- Tokenizers 0.13.2
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