transformers tensorboard safetensors distilbert text-classification generated_from_trainer en dataset:glue base_model:gokulsrinivasagan/bert_base_lda_50_v1_book base_model:finetune:gokulsrinivasagan/bert_base_lda_50_v1_book model-index autotrain_compatible endpoints_compatible region:us
---
base_model: gokulsrinivasagan/bert_base_lda_50_v1_book
datasets:
- glue
language:
- en
library_name: transformers
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: bert_base_lda_50_v1_book_mnli
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: GLUE MNLI
      type: glue
      args: mnli
    metrics:
    - type: accuracy
      value: 0.7977013832384052
      name: Accuracy
---

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# bert_base_lda_50_v1_book_mnli

This model is a fine-tuned version of [gokulsrinivasagan/bert_base_lda_50_v1_book](https://huggingface.co/gokulsrinivasagan/bert_base_lda_50_v1_book) on the GLUE MNLI dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5102
- Accuracy: 0.7977

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.695         | 1.0   | 1534  | 0.5630          | 0.7743   |
| 0.4907        | 2.0   | 3068  | 0.5236          | 0.7984   |
| 0.3874        | 3.0   | 4602  | 0.5264          | 0.8022   |
| 0.2906        | 4.0   | 6136  | 0.6159          | 0.8029   |
| 0.2185        | 5.0   | 7670  | 0.6220          | 0.8014   |
| 0.1658        | 6.0   | 9204  | 0.7832          | 0.8      |
| 0.1301        | 7.0   | 10738 | 0.7668          | 0.8019   |


### Framework versions

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