---
library_name: transformers
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- accuracy
model-index:
- name: classify
  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. -->

# classify

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: 0.5723
- Precision: 0.0
- Recall: 0.0
- F1 Binary: 0.0
- Accuracy: 0.7429

## 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: 0.0003
- train_batch_size: 4
- eval_batch_size: 4
- seed: 0
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Use OptimizerNames.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: 20

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Precision | Recall | F1 Binary | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:---------:|:------:|:---------:|:--------:|
| No log        | 0       | 0    | 0.7028          | 0.2437    | 0.7160 | 0.3636    | 0.3556   |
| 0.6           | 2.8181  | 1000 | 0.5779          | 0.0       | 0.0    | 0.0       | 0.7429   |
| 0.5522        | 5.6347  | 2000 | 0.5709          | 0.0       | 0.0    | 0.0       | 0.7429   |
| 0.5582        | 8.4513  | 3000 | 0.5709          | 0.0       | 0.0    | 0.0       | 0.7429   |
| 0.5791        | 11.2680 | 4000 | 0.5703          | 0.0       | 0.0    | 0.0       | 0.7429   |
| 0.5895        | 14.0846 | 5000 | 0.5701          | 0.0       | 0.0    | 0.0       | 0.7429   |
| 0.5629        | 16.9027 | 6000 | 0.5730          | 0.0       | 0.0    | 0.0       | 0.7429   |
| 0.5841        | 19.7193 | 7000 | 0.5723          | 0.0       | 0.0    | 0.0       | 0.7429   |


### Framework versions

- Transformers 4.48.1
- Pytorch 2.3.0
- Datasets 3.2.0
- Tokenizers 0.21.0