---
license: mit
tags:
- generated_from_trainer
datasets:
- stereoset
metrics:
- accuracy
model-index:
- name: stereoset_trainer_roberta-base_finetuned
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: stereoset
      type: stereoset
      config: intersentence
      split: validation
      args: intersentence
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.7535321821036107
---

<!-- 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. -->

# stereoset_trainer_roberta-base_finetuned

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the stereoset dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5749
- Accuracy: 0.7535

## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.54  | 50   | 0.6919          | 0.5157   |
| No log        | 1.08  | 100  | 0.6944          | 0.4843   |
| No log        | 1.61  | 150  | 0.6275          | 0.6664   |
| No log        | 2.15  | 200  | 0.5548          | 0.7355   |
| No log        | 2.69  | 250  | 0.5613          | 0.7331   |
| No log        | 3.23  | 300  | 0.6062          | 0.7331   |
| No log        | 3.76  | 350  | 0.5455          | 0.7488   |
| No log        | 4.3   | 400  | 0.6223          | 0.7488   |
| No log        | 4.84  | 450  | 0.5749          | 0.7535   |


### Framework versions

- Transformers 4.23.1
- Pytorch 1.12.1
- Datasets 2.6.1
- Tokenizers 0.13.1