---
library_name: transformers
language:
- en
base_model: Hartunka/bert_base_km_100_v1
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- spearmanr
model-index:
- name: bert_base_km_100_v1_stsb
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE STSB
      type: glue
      args: stsb
    metrics:
    - name: Spearmanr
      type: spearmanr
      value: 0.29833547420506246
---

<!-- 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_100_v1_stsb

This model is a fine-tuned version of [Hartunka/bert_base_km_100_v1](https://huggingface.co/Hartunka/bert_base_km_100_v1) on the GLUE STSB dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2490
- Pearson: 0.2995
- Spearmanr: 0.2983
- Combined Score: 0.2989

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 2.7396        | 1.0   | 23   | 2.5547          | 0.1514  | 0.1351    | 0.1432         |
| 1.9555        | 2.0   | 46   | 2.3166          | 0.1712  | 0.1497    | 0.1605         |
| 1.749         | 3.0   | 69   | 2.3146          | 0.2127  | 0.2000    | 0.2064         |
| 1.3865        | 4.0   | 92   | 2.2490          | 0.2995  | 0.2983    | 0.2989         |
| 0.9821        | 5.0   | 115  | 2.7978          | 0.2457  | 0.2364    | 0.2410         |
| 0.6935        | 6.0   | 138  | 2.8239          | 0.2598  | 0.2516    | 0.2557         |
| 0.4947        | 7.0   | 161  | 2.9618          | 0.2405  | 0.2309    | 0.2357         |
| 0.3874        | 8.0   | 184  | 2.7149          | 0.2566  | 0.2501    | 0.2533         |
| 0.31          | 9.0   | 207  | 2.5269          | 0.2768  | 0.2706    | 0.2737         |


### Framework versions

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