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---
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
|