---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- spearmanr
model-index:
- name: distilbert-base-uncased-finetuned-stsb
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: glue
      type: glue
      config: stsb
      split: validation
      args: stsb
    metrics:
    - name: Spearmanr
      type: spearmanr
      value: 0.8703919468681796
---

<!-- 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. -->

# distilbert-base-uncased-finetuned-stsb

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the glue dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5388
- Pearson: 0.8740
- Spearmanr: 0.8704

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Pearson | Spearmanr |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|
| No log        | 1.0   | 360  | 0.6683          | 0.8599  | 0.8575    |
| 1.0348        | 2.0   | 720  | 0.5413          | 0.8715  | 0.8685    |
| 0.3974        | 3.0   | 1080 | 0.5560          | 0.8725  | 0.8692    |
| 0.3974        | 4.0   | 1440 | 0.5666          | 0.8737  | 0.8703    |
| 0.2516        | 5.0   | 1800 | 0.5388          | 0.8740  | 0.8704    |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3