---
library_name: transformers
language:
- en
base_model: Hartunka/bert_base_km_50_v2
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- spearmanr
model-index:
- name: bert_base_km_50_v2_stsb
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE STSB
      type: glue
      args: stsb
    metrics:
    - name: Spearmanr
      type: spearmanr
      value: 0.2528909067613722
---

<!-- 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_v2_stsb

This model is a fine-tuned version of [Hartunka/bert_base_km_50_v2](https://huggingface.co/Hartunka/bert_base_km_50_v2) on the GLUE STSB dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2956
- Pearson: 0.2660
- Spearmanr: 0.2529
- Combined Score: 0.2595

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 2.863         | 1.0   | 23   | 2.9546          | 0.1062  | 0.1142    | 0.1102         |
| 1.9987        | 2.0   | 46   | 2.3012          | 0.2302  | 0.2091    | 0.2197         |
| 1.7872        | 3.0   | 69   | 2.2956          | 0.2660  | 0.2529    | 0.2595         |
| 1.5246        | 4.0   | 92   | 2.4771          | 0.2736  | 0.2569    | 0.2652         |
| 1.247         | 5.0   | 115  | 2.5712          | 0.2505  | 0.2352    | 0.2428         |
| 0.9895        | 6.0   | 138  | 2.4369          | 0.3222  | 0.3227    | 0.3225         |
| 0.77          | 7.0   | 161  | 2.3281          | 0.3366  | 0.3382    | 0.3374         |
| 0.6098        | 8.0   | 184  | 2.4814          | 0.3255  | 0.3204    | 0.3230         |


### Framework versions

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