---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
datasets:
- cosmos_qa
metrics:
- accuracy
model-index:
- name: bert-base-uncased-finetuned-cosmos
  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. -->

# bert-base-uncased-finetuned-cosmos

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the cosmos_qa dataset.
It achieves the following results on the evaluation set:
- Loss: 3.1272
- Accuracy: 0.5752

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.0246        | 1.0   | 6316  | 1.0667          | 0.5715   |
| 0.632         | 2.0   | 12632 | 1.5163          | 0.5926   |
| 0.2341        | 3.0   | 18948 | 3.1272          | 0.5752   |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.1.1+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2