FNet_Classification / README.md
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---
license: apache-2.0
base_model: google/fnet-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: FNet_Classification
results: []
---
<!-- 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_Classification
This model is a fine-tuned version of [google/fnet-base](https://huggingface.co/google/fnet-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3889
- Accuracy: 0.813
## 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: 2
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5529 | 1.0 | 625 | 0.4144 | 0.804 |
| 0.4314 | 2.0 | 1250 | 0.3889 | 0.813 |
### Framework versions
- Transformers 4.32.1
- Pytorch 2.2.1+cpu
- Datasets 2.12.0
- Tokenizers 0.13.2