---
library_name: transformers
language:
- en
license: apache-2.0
base_model: gokulsrinivasagan/tinybert_base_train_book_ent_15p_s_init
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: tinybert_base_train_book_ent_15p_s_init_qqp
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE QQP
      type: glue
      args: qqp
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8579520158298294
    - name: F1
      type: f1
      value: 0.8032073467429668
---

<!-- 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. -->

# tinybert_base_train_book_ent_15p_s_init_qqp

This model is a fine-tuned version of [gokulsrinivasagan/tinybert_base_train_book_ent_15p_s_init](https://huggingface.co/gokulsrinivasagan/tinybert_base_train_book_ent_15p_s_init) on the GLUE QQP dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3183
- Accuracy: 0.8580
- F1: 0.8032
- Combined Score: 0.8306

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:--------------:|
| 0.4585        | 1.0   | 1422  | 0.3807          | 0.8173   | 0.7658 | 0.7915         |
| 0.3589        | 2.0   | 2844  | 0.3712          | 0.8234   | 0.7913 | 0.8073         |
| 0.3115        | 3.0   | 4266  | 0.3361          | 0.8477   | 0.8112 | 0.8294         |
| 0.2742        | 4.0   | 5688  | 0.3183          | 0.8580   | 0.8032 | 0.8306         |
| 0.2431        | 5.0   | 7110  | 0.3297          | 0.8611   | 0.8162 | 0.8386         |
| 0.2161        | 6.0   | 8532  | 0.3238          | 0.8658   | 0.8248 | 0.8453         |
| 0.1931        | 7.0   | 9954  | 0.3438          | 0.8626   | 0.8242 | 0.8434         |
| 0.171         | 8.0   | 11376 | 0.3703          | 0.8672   | 0.8293 | 0.8482         |
| 0.1516        | 9.0   | 12798 | 0.3969          | 0.8628   | 0.8281 | 0.8455         |


### Framework versions

- Transformers 4.51.2
- Pytorch 2.6.0+cu126
- Datasets 3.5.0
- Tokenizers 0.21.1