---
library_name: transformers
language:
- en
base_model: Hartunka/distilbert_rand_50_v2
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- spearmanr
model-index:
- name: distilbert_rand_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: 0.23672264638416732
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# distilbert_rand_50_v2_stsb

This model is a fine-tuned version of [Hartunka/distilbert_rand_50_v2](https://huggingface.co/Hartunka/distilbert_rand_50_v2) on the GLUE STSB dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2659
- Pearson: 0.2493
- Spearmanr: 0.2367
- Combined Score: 0.2430

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 3.0153        | 1.0   | 23   | 2.4353          | 0.1203  | 0.1031    | 0.1117         |
| 1.9567        | 2.0   | 46   | 2.4981          | 0.1854  | 0.1692    | 0.1773         |
| 1.7232        | 3.0   | 69   | 2.2659          | 0.2493  | 0.2367    | 0.2430         |
| 1.4358        | 4.0   | 92   | 2.2973          | 0.2887  | 0.2818    | 0.2852         |
| 1.0785        | 5.0   | 115  | 2.6259          | 0.2453  | 0.2340    | 0.2396         |
| 0.7743        | 6.0   | 138  | 2.5245          | 0.2873  | 0.2825    | 0.2849         |
| 0.5991        | 7.0   | 161  | 2.6255          | 0.3081  | 0.3047    | 0.3064         |
| 0.479         | 8.0   | 184  | 2.6337          | 0.2887  | 0.2803    | 0.2845         |


### Framework versions

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