transformers tensorboard safetensors distilbert text-classification generated_from_trainer en dataset:glue base_model:gokulsrinivasagan/distilbert_lda_5_v1_book base_model:finetune:gokulsrinivasagan/distilbert_lda_5_v1_book model-index autotrain_compatible endpoints_compatible region:us
---
base_model: gokulsrinivasagan/distilbert_lda_5_v1_book
datasets:
- glue
language:
- en
library_name: transformers
metrics:
- accuracy
- f1
tags:
- generated_from_trainer
model-index:
- name: distilbert_lda_5_v1_book_mrpc
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: GLUE MRPC
      type: glue
      args: mrpc
    metrics:
    - type: accuracy
      value: 0.7254901960784313
      name: Accuracy
    - type: f1
      value: 0.8021201413427562
      name: F1
---

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# distilbert_lda_5_v1_book_mrpc

This model is a fine-tuned version of [gokulsrinivasagan/distilbert_lda_5_v1_book](https://huggingface.co/gokulsrinivasagan/distilbert_lda_5_v1_book) on the GLUE MRPC dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5515
- Accuracy: 0.7255
- F1: 0.8021
- Combined Score: 0.7638

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
| 0.6286        | 1.0   | 15   | 0.5986          | 0.6912   | 0.7987 | 0.7449         |
| 0.5813        | 2.0   | 30   | 0.5607          | 0.6961   | 0.8069 | 0.7515         |
| 0.5063        | 3.0   | 45   | 0.5515          | 0.7255   | 0.8021 | 0.7638         |
| 0.3879        | 4.0   | 60   | 0.7277          | 0.7157   | 0.8204 | 0.7681         |
| 0.2612        | 5.0   | 75   | 0.6235          | 0.7279   | 0.8083 | 0.7681         |
| 0.1772        | 6.0   | 90   | 0.8348          | 0.7377   | 0.8310 | 0.7844         |
| 0.1384        | 7.0   | 105  | 1.0297          | 0.7230   | 0.8270 | 0.7750         |
| 0.0807        | 8.0   | 120  | 0.9378          | 0.7402   | 0.8279 | 0.7841         |


### Framework versions

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