transformers tensorboard safetensors distilbert text-classification generated_from_trainer en dataset:glue base_model:gokulsrinivasagan/tinybert_train_book_v2 base_model:finetune:gokulsrinivasagan/tinybert_train_book_v2 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
base_model: gokulsrinivasagan/tinybert_train_book_v2
datasets:
- glue
language:
- en
library_name: transformers
license: apache-2.0
metrics:
- accuracy
- f1
tags:
- generated_from_trainer
model-index:
- name: tinybert_train_book_v2_qqp
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: GLUE QQP
      type: glue
      args: qqp
    metrics:
    - type: accuracy
      value: 0.8763047242146921
      name: Accuracy
    - type: f1
      value: 0.8292416430498173
      name: F1
---

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# tinybert_train_book_v2_qqp

This model is a fine-tuned version of [gokulsrinivasagan/tinybert_train_book_v2](https://huggingface.co/gokulsrinivasagan/tinybert_train_book_v2) on the GLUE QQP dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2906
- Accuracy: 0.8763
- F1: 0.8292
- Combined Score: 0.8528

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:--------------:|
| 0.397         | 1.0   | 1422  | 0.3445          | 0.8484   | 0.7789 | 0.8137         |
| 0.2958        | 2.0   | 2844  | 0.3029          | 0.8695   | 0.8221 | 0.8458         |
| 0.2432        | 3.0   | 4266  | 0.2906          | 0.8763   | 0.8292 | 0.8528         |
| 0.1995        | 4.0   | 5688  | 0.2984          | 0.8798   | 0.8315 | 0.8557         |
| 0.1629        | 5.0   | 7110  | 0.3093          | 0.8847   | 0.8454 | 0.8651         |
| 0.1334        | 6.0   | 8532  | 0.3454          | 0.8849   | 0.8435 | 0.8642         |
| 0.1097        | 7.0   | 9954  | 0.3595          | 0.8847   | 0.8452 | 0.8649         |
| 0.0925        | 8.0   | 11376 | 0.3933          | 0.8854   | 0.8441 | 0.8647         |


### Framework versions

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