---
library_name: transformers
license: apache-2.0
base_model: google-bert/bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert-base-uncased-answerable-or-not
  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-answerable-or-not

This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0575
- Accuracy: 0.9924

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.1654        | 1.0   | 198  | 0.1760          | 0.9494   |
| 0.1683        | 2.0   | 396  | 0.0854          | 0.9772   |
| 0.0003        | 3.0   | 594  | 0.0871          | 0.9848   |
| 0.0002        | 4.0   | 792  | 0.0575          | 0.9924   |
| 0.0001        | 5.0   | 990  | 0.0621          | 0.9899   |
| 0.0001        | 6.0   | 1188 | 0.0676          | 0.9899   |
| 0.0001        | 7.0   | 1386 | 0.0668          | 0.9899   |


### Framework versions

- Transformers 5.2.0
- Pytorch 2.10.0+cu128
- Datasets 4.5.0
- Tokenizers 0.22.2