---
library_name: transformers
language:
- en
base_model: Hartunka/distilbert_km_5_v2
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- spearmanr
model-index:
- name: distilbert_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: 0.42646563812642424
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# distilbert_km_5_v2_stsb

This model is a fine-tuned version of [Hartunka/distilbert_km_5_v2](https://huggingface.co/Hartunka/distilbert_km_5_v2) on the GLUE STSB dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9509
- Pearson: 0.4293
- Spearmanr: 0.4265
- Combined Score: 0.4279

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 2.855         | 1.0   | 23   | 2.3396          | 0.1598  | 0.1539    | 0.1568         |
| 1.8792        | 2.0   | 46   | 2.2082          | 0.2599  | 0.2485    | 0.2542         |
| 1.531         | 3.0   | 69   | 2.1020          | 0.3665  | 0.3604    | 0.3634         |
| 1.1221        | 4.0   | 92   | 1.9509          | 0.4293  | 0.4265    | 0.4279         |
| 0.7863        | 5.0   | 115  | 2.1921          | 0.4221  | 0.4242    | 0.4231         |
| 0.5364        | 6.0   | 138  | 2.1038          | 0.4496  | 0.4501    | 0.4498         |
| 0.4273        | 7.0   | 161  | 2.0297          | 0.4535  | 0.4503    | 0.4519         |
| 0.3516        | 8.0   | 184  | 2.1971          | 0.4279  | 0.4217    | 0.4248         |
| 0.2901        | 9.0   | 207  | 2.0682          | 0.4296  | 0.4233    | 0.4265         |


### Framework versions

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