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library_name: transformers
language:
- en
license: apache-2.0
base_model: gokulsrinivasagan/tinybert_base_train_kd
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: tinybert_base_train_kd_qqp
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE QQP
type: glue
args: qqp
metrics:
- name: Accuracy
type: accuracy
value: 0.8704922087558743
- name: F1
type: f1
value: 0.8217592592592593
---
<!-- 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_qqp
This model is a fine-tuned version of [gokulsrinivasagan/tinybert_base_train_kd](https://huggingface.co/gokulsrinivasagan/tinybert_base_train_kd) on the GLUE QQP dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3005
- Accuracy: 0.8705
- F1: 0.8218
- Combined Score: 0.8461
## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:--------------:|
| 0.4061 | 1.0 | 1422 | 0.3443 | 0.8430 | 0.7827 | 0.8129 |
| 0.3179 | 2.0 | 2844 | 0.3138 | 0.8611 | 0.8150 | 0.8381 |
| 0.269 | 3.0 | 4266 | 0.3077 | 0.8663 | 0.8258 | 0.8461 |
| 0.2275 | 4.0 | 5688 | 0.3005 | 0.8705 | 0.8218 | 0.8461 |
| 0.1923 | 5.0 | 7110 | 0.3269 | 0.8750 | 0.8254 | 0.8502 |
| 0.1614 | 6.0 | 8532 | 0.3224 | 0.8750 | 0.8291 | 0.8521 |
| 0.1349 | 7.0 | 9954 | 0.3559 | 0.8761 | 0.8387 | 0.8574 |
| 0.1132 | 8.0 | 11376 | 0.4348 | 0.8775 | 0.8324 | 0.8550 |
| 0.0966 | 9.0 | 12798 | 0.4351 | 0.8796 | 0.8394 | 0.8595 |
### Framework versions
- Transformers 4.51.2
- Pytorch 2.6.0+cu126
- Datasets 3.5.0
- Tokenizers 0.21.1
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