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library_name: transformers
language:
- en
base_model: Hartunka/tiny_bert_km_20_v1
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: tiny_bert_km_20_v1_mrpc
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE MRPC
type: glue
args: mrpc
metrics:
- name: Accuracy
type: accuracy
value: 0.7156862745098039
- name: F1
type: f1
value: 0.8204334365325078
---
<!-- 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_20_v1_mrpc
This model is a fine-tuned version of [Hartunka/tiny_bert_km_20_v1](https://huggingface.co/Hartunka/tiny_bert_km_20_v1) on the GLUE MRPC dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5803
- Accuracy: 0.7157
- F1: 0.8204
- Combined Score: 0.7681
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
| 0.6272 | 1.0 | 15 | 0.5963 | 0.6961 | 0.8075 | 0.7518 |
| 0.5912 | 2.0 | 30 | 0.5992 | 0.6961 | 0.8160 | 0.7561 |
| 0.5662 | 3.0 | 45 | 0.5904 | 0.7157 | 0.8253 | 0.7705 |
| 0.5452 | 4.0 | 60 | 0.5803 | 0.7157 | 0.8204 | 0.7681 |
| 0.5011 | 5.0 | 75 | 0.5830 | 0.7279 | 0.8207 | 0.7743 |
| 0.4413 | 6.0 | 90 | 0.6183 | 0.7059 | 0.7931 | 0.7495 |
| 0.3632 | 7.0 | 105 | 0.6797 | 0.6961 | 0.7926 | 0.7444 |
| 0.2641 | 8.0 | 120 | 0.7895 | 0.7108 | 0.8013 | 0.7561 |
| 0.1796 | 9.0 | 135 | 0.8991 | 0.6912 | 0.7805 | 0.7358 |
### Framework versions
- Transformers 4.50.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.21.1
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