---
library_name: transformers
base_model: gokulsrinivasagan/bert_base_lda_100_v1
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert_base_lda_100_v1_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_100_v1_wnli

This model is a fine-tuned version of [gokulsrinivasagan/bert_base_lda_100_v1](https://huggingface.co/gokulsrinivasagan/bert_base_lda_100_v1) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6907
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.9555        | 1.0   | 3    | 1.7839          | 0.5634   |
| 1.287         | 2.0   | 6    | 1.9711          | 0.5634   |
| 1.9411        | 3.0   | 9    | 0.7586          | 0.5634   |
| 0.8928        | 4.0   | 12   | 0.9855          | 0.4366   |
| 0.8147        | 5.0   | 15   | 0.7992          | 0.5634   |
| 0.8064        | 6.0   | 18   | 0.6987          | 0.4366   |
| 0.7033        | 7.0   | 21   | 0.6914          | 0.5634   |
| 0.7235        | 8.0   | 24   | 0.6867          | 0.5634   |
| 0.701         | 9.0   | 27   | 0.7205          | 0.4366   |
| 0.6954        | 10.0  | 30   | 0.6856          | 0.5634   |
| 0.6999        | 11.0  | 33   | 0.6916          | 0.5634   |
| 0.7008        | 12.0  | 36   | 0.7042          | 0.4366   |
| 0.6948        | 13.0  | 39   | 0.6856          | 0.5634   |
| 0.6948        | 14.0  | 42   | 0.6864          | 0.5634   |
| 0.6946        | 15.0  | 45   | 0.6907          | 0.5634   |


### Framework versions

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