---
library_name: transformers
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
model-index:
- name: bert-base-uncased-pp-200000-1e-06-64
  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. -->

# bert-base-uncased-pp-200000-1e-06-64

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co./bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6662

## 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: 1e-06
- train_batch_size: 256
- eval_batch_size: 1024
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 0.6913        | 1.0   | 782   | 0.6818          |
| 0.6853        | 2.0   | 1564  | 0.6759          |
| 0.6819        | 3.0   | 2346  | 0.6728          |
| 0.6791        | 4.0   | 3128  | 0.6708          |
| 0.6789        | 5.0   | 3910  | 0.6689          |
| 0.6757        | 6.0   | 4692  | 0.6678          |
| 0.6741        | 7.0   | 5474  | 0.6673          |
| 0.6748        | 8.0   | 6256  | 0.6668          |
| 0.6728        | 9.0   | 7038  | 0.6664          |
| 0.6723        | 10.0  | 7820  | 0.6664          |
| 0.6696        | 11.0  | 8602  | 0.6668          |
| 0.668         | 12.0  | 9384  | 0.6662          |
| 0.6681        | 13.0  | 10166 | 0.6669          |
| 0.6658        | 14.0  | 10948 | 0.6667          |
| 0.6666        | 15.0  | 11730 | 0.6669          |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1