---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: scenario-KD-SCR-DIV2-data-glue-qnli-model-bert-base-uncased-run-1
  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. -->

# scenario-KD-SCR-DIV2-data-glue-qnli-model-bert-base-uncased-run-1

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7514
- Accuracy: 0.8627

## 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: 16
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6969

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 2.4263        | 1.0   | 3273  | 1.6907          | 0.8545   |
| 1.7748        | 2.0   | 6547  | 1.8491          | 0.8499   |
| 1.1414        | 3.0   | 9820  | 1.9422          | 0.8545   |
| 0.8965        | 4.0   | 13094 | 1.7533          | 0.8552   |
| 0.7756        | 5.0   | 16367 | 1.7103          | 0.8570   |
| 0.6527        | 6.0   | 19641 | 1.6665          | 0.8569   |
| 0.6056        | 7.0   | 22914 | 1.5879          | 0.8620   |
| 0.5559        | 8.0   | 26188 | 1.6570          | 0.8618   |
| 0.5154        | 9.0   | 29461 | 1.5519          | 0.8658   |
| 0.4752        | 10.0  | 32735 | 1.6905          | 0.8612   |
| 0.4581        | 11.0  | 36008 | 1.6075          | 0.8644   |
| 0.4322        | 12.0  | 39282 | 1.6963          | 0.8614   |
| 0.3969        | 13.0  | 42555 | 1.6467          | 0.8660   |
| 0.393         | 14.0  | 45829 | 1.6735          | 0.8680   |
| 0.3651        | 15.0  | 49102 | 1.7631          | 0.8614   |
| 0.3464        | 16.0  | 52376 | 1.7957          | 0.8645   |
| 0.3455        | 17.0  | 55649 | 1.7008          | 0.8680   |
| 0.3276        | 18.0  | 58923 | 1.7183          | 0.8669   |
| 0.3239        | 19.0  | 62196 | 1.7514          | 0.8627   |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.2
- Datasets 2.16.0
- Tokenizers 0.15.0