---
library_name: transformers
language:
- en
license: apache-2.0
base_model: gokulsrinivasagan/tinybert_base_train_kd
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: tinybert_base_train_kd_mnli
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE MNLI
      type: glue
      args: mnli
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.7617982099267697
---

<!-- 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_kd_mnli

This model is a fine-tuned version of [gokulsrinivasagan/tinybert_base_train_kd](https://huggingface.co/gokulsrinivasagan/tinybert_base_train_kd) on the GLUE MNLI dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5858
- Accuracy: 0.7618

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.8098        | 1.0   | 1534  | 0.7137          | 0.6905   |
| 0.6666        | 2.0   | 3068  | 0.6576          | 0.7277   |
| 0.5873        | 3.0   | 4602  | 0.6274          | 0.7377   |
| 0.522         | 4.0   | 6136  | 0.6076          | 0.7493   |
| 0.4623        | 5.0   | 7670  | 0.6133          | 0.7570   |
| 0.4069        | 6.0   | 9204  | 0.6448          | 0.7575   |
| 0.3547        | 7.0   | 10738 | 0.6818          | 0.7606   |
| 0.3073        | 8.0   | 12272 | 0.7034          | 0.7603   |
| 0.2658        | 9.0   | 13806 | 0.8077          | 0.7490   |


### Framework versions

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