---
license: apache-2.0
base_model: google-bert/bert-base-uncased
tags:
- generated_from_trainer
model-index:
- name: Google_bert-base-uncased
  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. -->

[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/dhanishetty-personaluse/huggingface/runs/5uvs4op2)
# Google_bert-base-uncased

This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0596

## 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
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: inverse_sqrt
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.2234        | 0.024 | 30   | 0.9557          |
| 0.4601        | 0.048 | 60   | 0.4359          |
| 0.3149        | 0.072 | 90   | 0.2795          |
| 0.2403        | 0.096 | 120  | 0.2142          |
| 0.1876        | 0.12  | 150  | 0.1714          |
| 0.1691        | 0.144 | 180  | 0.1488          |
| 0.1394        | 0.168 | 210  | 0.1273          |
| 0.1264        | 0.192 | 240  | 0.1160          |
| 0.1113        | 0.216 | 270  | 0.1079          |
| 0.1148        | 0.24  | 300  | 0.0992          |
| 0.0995        | 0.264 | 330  | 0.0940          |
| 0.096         | 0.288 | 360  | 0.0941          |
| 0.0954        | 0.312 | 390  | 0.0854          |
| 0.089         | 0.336 | 420  | 0.0899          |
| 0.0826        | 0.36  | 450  | 0.0841          |
| 0.0872        | 0.384 | 480  | 0.0811          |
| 0.0794        | 0.408 | 510  | 0.0759          |
| 0.0756        | 0.432 | 540  | 0.0766          |
| 0.0826        | 0.456 | 570  | 0.0729          |
| 0.0841        | 0.48  | 600  | 0.0715          |
| 0.076         | 0.504 | 630  | 0.0737          |
| 0.0746        | 0.528 | 660  | 0.0691          |
| 0.0719        | 0.552 | 690  | 0.0697          |
| 0.0722        | 0.576 | 720  | 0.0673          |
| 0.0713        | 0.6   | 750  | 0.0656          |
| 0.0671        | 0.624 | 780  | 0.0652          |
| 0.0741        | 0.648 | 810  | 0.0675          |
| 0.0723        | 0.672 | 840  | 0.0663          |
| 0.0687        | 0.696 | 870  | 0.0649          |
| 0.067         | 0.72  | 900  | 0.0637          |
| 0.0623        | 0.744 | 930  | 0.0643          |
| 0.0599        | 0.768 | 960  | 0.0643          |
| 0.0686        | 0.792 | 990  | 0.0624          |
| 0.0638        | 0.816 | 1020 | 0.0623          |
| 0.0565        | 0.84  | 1050 | 0.0626          |
| 0.0614        | 0.864 | 1080 | 0.0615          |
| 0.063         | 0.888 | 1110 | 0.0592          |
| 0.0592        | 0.912 | 1140 | 0.0618          |
| 0.0687        | 0.936 | 1170 | 0.0618          |
| 0.0577        | 0.96  | 1200 | 0.0600          |
| 0.0629        | 0.984 | 1230 | 0.0596          |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.3.1+cu118
- Datasets 2.20.0
- Tokenizers 0.19.1