---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: 2d_psn_1600
  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. -->

# 2d_psn_1600

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the [ComNum](https://huggingface.co/datasets/abbassix/ComNum) dataset.
This model used 800 samples as training, 200 as validation, and 1200 as test on three epochs.
It achieves the following results on the evaluation set:
- Loss: 0.3675
- Accuracy: 0.7175

This model achieves the following results on the test set:
- Loss: 0.3475
- Accuracy: 0.7493
<!--
{'eval_loss': 0.34749719500541687, 'eval_accuracy': 0.7493, 'eval_runtime': 852.7429, 'eval_samples_per_second': 11.727, 'eval_steps_per_second': 1.466}
-->
## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 200  | 0.3701          | 0.735    |
| No log        | 2.0   | 400  | 0.3714          | 0.74     |
| 0.4173        | 3.0   | 600  | 0.3675          | 0.7175   |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0