---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
base_model: bert-base-uncased
model-index:
- name: EquityVsDebtIssue
  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. -->

# EquityVsDebtIssue

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: 0.4756
- Accuracy: 0.7940

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5713        | 1.0   | 949  | 0.4617          | 0.7808   |
| 0.3993        | 2.0   | 1898 | 0.4756          | 0.7940   |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.0
- Datasets 2.6.1
- Tokenizers 0.11.0