---
library_name: transformers
language:
- en
base_model: Hartunka/bert_base_km_20_v1
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- spearmanr
model-index:
- name: bert_base_km_20_v1_stsb
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE STSB
      type: glue
      args: stsb
    metrics:
    - name: Spearmanr
      type: spearmanr
      value: 0.2806848266082787
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# bert_base_km_20_v1_stsb

This model is a fine-tuned version of [Hartunka/bert_base_km_20_v1](https://huggingface.co/Hartunka/bert_base_km_20_v1) on the GLUE STSB dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1734
- Pearson: 0.2765
- Spearmanr: 0.2807
- Combined Score: 0.2786

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 2.7536        | 1.0   | 23   | 2.3629          | 0.2232  | 0.2145    | 0.2188         |
| 2.0466        | 2.0   | 46   | 2.2233          | 0.2264  | 0.2236    | 0.2250         |
| 1.83          | 3.0   | 69   | 2.1734          | 0.2765  | 0.2807    | 0.2786         |
| 1.488         | 4.0   | 92   | 2.2847          | 0.2848  | 0.2866    | 0.2857         |
| 1.1184        | 5.0   | 115  | 2.7559          | 0.2705  | 0.2897    | 0.2801         |
| 0.836         | 6.0   | 138  | 2.4744          | 0.3009  | 0.3170    | 0.3090         |
| 0.5651        | 7.0   | 161  | 2.5625          | 0.2950  | 0.3011    | 0.2981         |
| 0.4161        | 8.0   | 184  | 2.4996          | 0.3085  | 0.3151    | 0.3118         |


### Framework versions

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