---
language:
- en
base_model: Hartunka/tiny_bert_km_50_v1
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- spearmanr
model-index:
- name: tiny_bert_km_50_v1_stsb
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE STSB
      type: glue
      args: stsb
    metrics:
    - name: Spearmanr
      type: spearmanr
      value: 0.18233475301431837
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# tiny_bert_km_50_v1_stsb

This model is a fine-tuned version of [Hartunka/tiny_bert_km_50_v1](https://huggingface.co/Hartunka/tiny_bert_km_50_v1) on the GLUE STSB dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2276
- Pearson: 0.1924
- Spearmanr: 0.1823
- Combined Score: 0.1873

## 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 | Pearson | Spearmanr | Combined Score |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 3.8515        | 1.0   | 23   | 2.2276          | 0.1924  | 0.1823    | 0.1873         |
| 2.1315        | 2.0   | 46   | 2.2514          | 0.2165  | 0.2014    | 0.2089         |
| 1.9864        | 3.0   | 69   | 2.2711          | 0.1966  | 0.1884    | 0.1925         |
| 1.8498        | 4.0   | 92   | 2.3629          | 0.2217  | 0.2164    | 0.2190         |
| 1.6182        | 5.0   | 115  | 2.3719          | 0.2448  | 0.2459    | 0.2454         |
| 1.3745        | 6.0   | 138  | 2.4489          | 0.2402  | 0.2417    | 0.2409         |


### Framework versions

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