---
library_name: transformers
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert-base-uncased-finetuned-set_5
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# bert-base-uncased-finetuned-set_5

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3627
- Accuracy: 0.8690
- Qwk: 0.8044

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Qwk    |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log        | 1.0   | 92   | 0.4092          | 0.8542   | 0.6368 |
| No log        | 2.0   | 184  | 0.3892          | 0.8452   | 0.7958 |
| No log        | 3.0   | 276  | 0.3484          | 0.8512   | 0.7103 |
| No log        | 4.0   | 368  | 0.3624          | 0.8452   | 0.7737 |
| No log        | 5.0   | 460  | 0.3627          | 0.8690   | 0.8044 |


### Framework versions

- Transformers 4.49.0
- Pytorch 2.6.0+cu124
- Datasets 3.3.1
- Tokenizers 0.21.0