---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased-finetuned-winogrande
  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. -->

# distilbert-base-uncased-finetuned-winogrande

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9100
- Accuracy: 0.5525

## 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: 1e-05
- train_batch_size: 8
- eval_batch_size: 4
- seed: 11262
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 4000
- num_epochs: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 1156 | 0.6931          | 0.5036   |
| No log        | 2.0   | 2312 | 0.6926          | 0.5067   |
| No log        | 3.0   | 3468 | 0.6929          | 0.5075   |
| No log        | 4.0   | 4624 | 0.6908          | 0.5272   |
| 0.6934        | 5.0   | 5780 | 0.6982          | 0.5391   |
| 0.6934        | 6.0   | 6936 | 0.7557          | 0.5312   |
| 0.6934        | 7.0   | 8092 | 0.8402          | 0.5478   |
| 0.6934        | 8.0   | 9248 | 0.9100          | 0.5525   |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cpu
- Datasets 2.10.1
- Tokenizers 0.13.2