---
library_name: transformers
base_model: gokulsrinivasagan/bert_base_lda_5
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert_base_lda_5_wnli
  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_lda_5_wnli

This model is a fine-tuned version of [gokulsrinivasagan/bert_base_lda_5](https://huggingface.co/gokulsrinivasagan/bert_base_lda_5) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6926
- Accuracy: 0.5634

## 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: 0.001
- train_batch_size: 256
- eval_batch_size: 256
- seed: 10
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.121         | 1.0   | 3    | 0.8205          | 0.5634   |
| 1.6034        | 2.0   | 6    | 1.7293          | 0.4366   |
| 0.9483        | 3.0   | 9    | 0.7649          | 0.4366   |
| 0.7514        | 4.0   | 12   | 0.7557          | 0.5634   |
| 0.746         | 5.0   | 15   | 0.8105          | 0.4366   |
| 0.7896        | 6.0   | 18   | 0.7383          | 0.4366   |
| 0.7573        | 7.0   | 21   | 0.6853          | 0.5634   |
| 0.6951        | 8.0   | 24   | 0.8346          | 0.4366   |
| 0.746         | 9.0   | 27   | 0.6906          | 0.5634   |
| 0.6992        | 10.0  | 30   | 0.6849          | 0.5634   |
| 0.6942        | 11.0  | 33   | 0.7009          | 0.4366   |
| 0.7           | 12.0  | 36   | 0.6951          | 0.4366   |
| 0.6976        | 13.0  | 39   | 0.6854          | 0.5634   |
| 0.6999        | 14.0  | 42   | 0.6901          | 0.5634   |
| 0.6948        | 15.0  | 45   | 0.6926          | 0.5634   |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.2.1+cu118
- Datasets 2.17.0
- Tokenizers 0.20.3