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library_name: transformers
language:
- en
base_model: Hartunka/tiny_bert_km_5_v1
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: tiny_bert_km_5_v1_qqp
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE QQP
type: glue
args: qqp
metrics:
- name: Accuracy
type: accuracy
value: 0.8229037843185754
- name: F1
type: f1
value: 0.7561474014031742
---
<!-- 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. -->
# tiny_bert_km_5_v1_qqp
This model is a fine-tuned version of [Hartunka/tiny_bert_km_5_v1](https://huggingface.co/Hartunka/tiny_bert_km_5_v1) on the GLUE QQP dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3982
- Accuracy: 0.8229
- F1: 0.7561
- Combined Score: 0.7895
## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:--------------:|
| 0.4854 | 1.0 | 1422 | 0.4320 | 0.7934 | 0.7100 | 0.7517 |
| 0.3893 | 2.0 | 2844 | 0.4019 | 0.8130 | 0.7421 | 0.7775 |
| 0.3257 | 3.0 | 4266 | 0.3982 | 0.8229 | 0.7561 | 0.7895 |
| 0.2734 | 4.0 | 5688 | 0.4342 | 0.8248 | 0.7447 | 0.7847 |
| 0.2309 | 5.0 | 7110 | 0.4551 | 0.8302 | 0.7638 | 0.7970 |
| 0.1964 | 6.0 | 8532 | 0.4515 | 0.8269 | 0.7721 | 0.7995 |
| 0.1681 | 7.0 | 9954 | 0.4995 | 0.8293 | 0.7751 | 0.8022 |
| 0.146 | 8.0 | 11376 | 0.5505 | 0.8304 | 0.7759 | 0.8031 |
### Framework versions
- Transformers 4.50.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.21.1
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