---
license: mit
tags:
- generated_from_trainer
datasets:
- crows_pairs
metrics:
- accuracy
model-index:
- name: crowspairs_trainer_roberta-large_finetuned
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: crows_pairs
      type: crows_pairs
      config: crows_pairs
      split: test
      args: crows_pairs
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.4966887417218543
---

<!-- 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. -->

# crowspairs_trainer_roberta-large_finetuned

This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on the crows_pairs dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6933
- Accuracy: 0.4967

## 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        | 0.53  | 20   | 0.6942          | 0.5033   |
| No log        | 1.05  | 40   | 0.6943          | 0.4967   |
| No log        | 1.58  | 60   | 0.7100          | 0.4967   |
| No log        | 2.11  | 80   | 0.6937          | 0.4967   |
| No log        | 2.63  | 100  | 0.6937          | 0.4967   |
| No log        | 3.16  | 120  | 0.6936          | 0.4967   |
| No log        | 3.68  | 140  | 0.6931          | 0.5033   |
| No log        | 4.21  | 160  | 0.6938          | 0.4967   |
| No log        | 4.74  | 180  | 0.6933          | 0.4967   |


### Framework versions

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