---
library_name: transformers
language:
- en
base_model: Hartunka/bert_base_km_50_v1
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- spearmanr
model-index:
- name: bert_base_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: 0.2801121104631292
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# bert_base_km_50_v1_stsb

This model is a fine-tuned version of [Hartunka/bert_base_km_50_v1](https://huggingface.co/Hartunka/bert_base_km_50_v1) on the GLUE STSB dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1389
- Pearson: 0.2763
- Spearmanr: 0.2801
- Combined Score: 0.2782

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 2.8402        | 1.0   | 23   | 2.4773          | 0.2068  | 0.2019    | 0.2043         |
| 2.0586        | 2.0   | 46   | 2.2433          | 0.2277  | 0.2264    | 0.2270         |
| 1.8469        | 3.0   | 69   | 2.1389          | 0.2763  | 0.2801    | 0.2782         |
| 1.5476        | 4.0   | 92   | 2.3079          | 0.2832  | 0.2836    | 0.2834         |
| 1.1654        | 5.0   | 115  | 2.3808          | 0.3015  | 0.3023    | 0.3019         |
| 0.8754        | 6.0   | 138  | 2.5276          | 0.2769  | 0.2751    | 0.2760         |
| 0.6215        | 7.0   | 161  | 2.4822          | 0.2907  | 0.2896    | 0.2901         |
| 0.4911        | 8.0   | 184  | 2.5762          | 0.3056  | 0.3060    | 0.3058         |


### Framework versions

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