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---
library_name: transformers
language:
- en
base_model: Hartunka/tiny_bert_km_10_v2
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- spearmanr
model-index:
- name: tiny_bert_km_10_v2_stsb
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE STSB
      type: glue
      args: stsb
    metrics:
    - name: Spearmanr
      type: spearmanr
      value: 0.10436822016561782
---

<!-- 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_10_v2_stsb

This model is a fine-tuned version of [Hartunka/tiny_bert_km_10_v2](https://huggingface.co/Hartunka/tiny_bert_km_10_v2) on the GLUE STSB dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2310
- Pearson: 0.1086
- Spearmanr: 0.1044
- Combined Score: 0.1065

## 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 | Pearson | Spearmanr | Combined Score |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 3.4768        | 1.0   | 23   | 2.2310          | 0.1086  | 0.1044    | 0.1065         |
| 2.0479        | 2.0   | 46   | 2.4443          | 0.1667  | 0.1616    | 0.1642         |
| 1.9049        | 3.0   | 69   | 2.2881          | 0.2178  | 0.2000    | 0.2089         |
| 1.7247        | 4.0   | 92   | 2.4857          | 0.2841  | 0.2727    | 0.2784         |
| 1.4995        | 5.0   | 115  | 2.2998          | 0.2949  | 0.2830    | 0.2890         |
| 1.2606        | 6.0   | 138  | 2.3140          | 0.3267  | 0.3195    | 0.3231         |


### Framework versions

- Transformers 4.50.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.21.1