transformers tensorboard safetensors distilbert text-classification generated_from_trainer en dataset:glue base_model:gokulsrinivasagan/bert_tiny_lda_book base_model:finetune:gokulsrinivasagan/bert_tiny_lda_book model-index autotrain_compatible endpoints_compatible region:us
---
base_model: gokulsrinivasagan/bert_tiny_lda_book
datasets:
- glue
language:
- en
library_name: transformers
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: bert_tiny_lda_book_qnli
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: GLUE QNLI
      type: glue
      args: qnli
    metrics:
    - type: accuracy
      value: 0.8261028738788212
      name: Accuracy
---

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# bert_tiny_lda_book_qnli

This model is a fine-tuned version of [gokulsrinivasagan/bert_tiny_lda_book](https://huggingface.co/gokulsrinivasagan/bert_tiny_lda_book) on the GLUE QNLI dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3910
- Accuracy: 0.8261

## 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: 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5188        | 1.0   | 410  | 0.4174          | 0.8093   |
| 0.4093        | 2.0   | 820  | 0.4038          | 0.8159   |
| 0.3459        | 3.0   | 1230 | 0.3910          | 0.8261   |
| 0.2907        | 4.0   | 1640 | 0.4633          | 0.8102   |
| 0.2369        | 5.0   | 2050 | 0.4564          | 0.8228   |
| 0.1936        | 6.0   | 2460 | 0.4939          | 0.8268   |
| 0.156         | 7.0   | 2870 | 0.5934          | 0.8122   |
| 0.1277        | 8.0   | 3280 | 0.6393          | 0.8098   |


### Framework versions

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