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---
library_name: transformers
language:
- en
base_model: gokulsrinivasagan/distilbert_lda_100_v1_book
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: distilbert_lda_100_v1_book_mrpc
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE MRPC
      type: glue
      args: mrpc
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.6911764705882353
    - name: F1
      type: f1
      value: 0.8061538461538461
---

<!-- 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. -->

# distilbert_lda_100_v1_book_mrpc

This model is a fine-tuned version of [gokulsrinivasagan/distilbert_lda_100_v1_book](https://huggingface.co/gokulsrinivasagan/distilbert_lda_100_v1_book) on the GLUE MRPC dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5726
- Accuracy: 0.6912
- F1: 0.8062
- Combined Score: 0.7487

## 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 OptimizerNames.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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
| 0.6251        | 1.0   | 15   | 0.5960          | 0.6838   | 0.8054 | 0.7446         |
| 0.5807        | 2.0   | 30   | 0.5726          | 0.6912   | 0.8062 | 0.7487         |
| 0.516         | 3.0   | 45   | 0.5825          | 0.7181   | 0.8223 | 0.7702         |
| 0.4062        | 4.0   | 60   | 0.5988          | 0.7255   | 0.8108 | 0.7682         |
| 0.2808        | 5.0   | 75   | 0.6600          | 0.7525   | 0.8279 | 0.7902         |
| 0.1683        | 6.0   | 90   | 0.9784          | 0.7353   | 0.8302 | 0.7827         |
| 0.1568        | 7.0   | 105  | 0.9396          | 0.7328   | 0.8239 | 0.7784         |


### Framework versions

- Transformers 4.46.1
- Pytorch 2.2.0+cu121
- Datasets 3.1.0
- Tokenizers 0.20.1