---
library_name: transformers
language:
- en
base_model: Hartunka/bert_base_km_5_v2
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- spearmanr
model-index:
- name: bert_base_km_5_v2_stsb
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE STSB
      type: glue
      args: stsb
    metrics:
    - name: Spearmanr
      type: spearmanr
      value: 0.4647300879795164
---

<!-- 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. -->

# bert_base_km_5_v2_stsb

This model is a fine-tuned version of [Hartunka/bert_base_km_5_v2](https://huggingface.co/Hartunka/bert_base_km_5_v2) on the GLUE STSB dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8177
- Pearson: 0.4729
- Spearmanr: 0.4647
- Combined Score: 0.4688

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 2.6459        | 1.0   | 23   | 2.4966          | 0.1835  | 0.1715    | 0.1775         |
| 1.8235        | 2.0   | 46   | 2.2914          | 0.3594  | 0.3550    | 0.3572         |
| 1.4306        | 3.0   | 69   | 2.0514          | 0.4242  | 0.4267    | 0.4254         |
| 1.0154        | 4.0   | 92   | 1.8177          | 0.4729  | 0.4647    | 0.4688         |
| 0.6595        | 5.0   | 115  | 2.1356          | 0.4311  | 0.4288    | 0.4299         |
| 0.5214        | 6.0   | 138  | 2.0065          | 0.4628  | 0.4615    | 0.4621         |
| 0.3787        | 7.0   | 161  | 2.2221          | 0.4495  | 0.4408    | 0.4451         |
| 0.3169        | 8.0   | 184  | 2.1129          | 0.4652  | 0.4569    | 0.4611         |
| 0.2679        | 9.0   | 207  | 2.1071          | 0.4559  | 0.4422    | 0.4491         |


### Framework versions

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