transformers tensorboard safetensors distilbert text-classification generated_from_trainer en dataset:glue base_model:gokulsrinivasagan/bert_base_lda_book base_model:finetune:gokulsrinivasagan/bert_base_lda_book model-index autotrain_compatible endpoints_compatible region:us
---
base_model: gokulsrinivasagan/bert_base_lda_book
datasets:
- glue
language:
- en
library_name: transformers
metrics:
- accuracy
- f1
tags:
- generated_from_trainer
model-index:
- name: bert_base_lda_book_mrpc
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: GLUE MRPC
      type: glue
      args: mrpc
    metrics:
    - type: accuracy
      value: 0.7475490196078431
      name: Accuracy
    - type: f1
      value: 0.8377952755905512
      name: F1
---

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# bert_base_lda_book_mrpc

This model is a fine-tuned version of [gokulsrinivasagan/bert_base_lda_book](https://huggingface.co/gokulsrinivasagan/bert_base_lda_book) on the GLUE MRPC dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4956
- Accuracy: 0.7475
- F1: 0.8378
- Combined Score: 0.7927

## 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 | F1     | Combined Score |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
| 0.6155        | 1.0   | 15   | 0.6025          | 0.6765   | 0.7807 | 0.7286         |
| 0.572         | 2.0   | 30   | 0.5528          | 0.75     | 0.8191 | 0.7846         |
| 0.5282        | 3.0   | 45   | 0.4956          | 0.7475   | 0.8378 | 0.7927         |
| 0.3932        | 4.0   | 60   | 0.5864          | 0.7721   | 0.8526 | 0.8123         |
| 0.2669        | 5.0   | 75   | 0.5059          | 0.8015   | 0.8639 | 0.8327         |
| 0.1739        | 6.0   | 90   | 0.6114          | 0.7966   | 0.8610 | 0.8288         |
| 0.0909        | 7.0   | 105  | 0.8679          | 0.7745   | 0.8540 | 0.8142         |
| 0.0558        | 8.0   | 120  | 0.6653          | 0.7966   | 0.8494 | 0.8230         |


### Framework versions

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