---
library_name: transformers
language:
- en
base_model: gokulsrinivasagan/bert_base_lda
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: bert_base_lda_wnli
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE WNLI
      type: glue
      args: wnli
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.5633802816901409
---

<!-- 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_wnli

This model is a fine-tuned version of [gokulsrinivasagan/bert_base_lda](https://huggingface.co/gokulsrinivasagan/bert_base_lda) on the GLUE WNLI dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6864
- 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: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.1638        | 1.0   | 3    | 1.4608          | 0.5634   |
| 1.0198        | 2.0   | 6    | 1.1097          | 0.5634   |
| 1.1474        | 3.0   | 9    | 0.8995          | 0.5634   |
| 0.8846        | 4.0   | 12   | 0.8201          | 0.4366   |
| 0.7886        | 5.0   | 15   | 0.6994          | 0.4366   |
| 0.738         | 6.0   | 18   | 0.7087          | 0.5634   |
| 0.7195        | 7.0   | 21   | 0.7214          | 0.4366   |
| 0.7036        | 8.0   | 24   | 0.6931          | 0.5634   |
| 0.6935        | 9.0   | 27   | 0.6896          | 0.5634   |
| 0.6941        | 10.0  | 30   | 0.6926          | 0.5634   |
| 0.6949        | 11.0  | 33   | 0.6936          | 0.4366   |
| 0.6959        | 12.0  | 36   | 0.6911          | 0.5634   |
| 0.6927        | 13.0  | 39   | 0.6864          | 0.5634   |
| 0.6928        | 14.0  | 42   | 0.6893          | 0.5634   |
| 0.6958        | 15.0  | 45   | 0.6896          | 0.5634   |
| 0.6936        | 16.0  | 48   | 0.6911          | 0.5634   |
| 0.6955        | 17.0  | 51   | 0.6911          | 0.5634   |
| 0.6939        | 18.0  | 54   | 0.6906          | 0.5634   |


### Framework versions

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