---
language:
- en
base_model: Hartunka/tiny_bert_km_100_v1
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
model-index:
- name: tiny_bert_km_100_v1_rte
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE RTE
      type: glue
      args: rte
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.5270758122743683
---

<!-- 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_100_v1_rte

This model is a fine-tuned version of [Hartunka/tiny_bert_km_100_v1](https://huggingface.co/Hartunka/tiny_bert_km_100_v1) on the GLUE RTE dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6949
- Accuracy: 0.5271

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.699         | 1.0   | 10   | 0.6959          | 0.5271   |
| 0.6852        | 2.0   | 20   | 0.7013          | 0.4982   |
| 0.6713        | 3.0   | 30   | 0.6949          | 0.5271   |
| 0.6531        | 4.0   | 40   | 0.7031          | 0.5451   |
| 0.6265        | 5.0   | 50   | 0.7080          | 0.5235   |
| 0.5887        | 6.0   | 60   | 0.7480          | 0.5162   |
| 0.5347        | 7.0   | 70   | 0.7833          | 0.5343   |
| 0.457         | 8.0   | 80   | 0.8417          | 0.5307   |


### Framework versions

- Transformers 4.40.0
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.19.1