---
language:
- en
base_model: google-t5/t5-base
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- spearmanr
model-index:
- name: STSB
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE STSB
      type: glue
      args: stsb
    metrics:
    - name: Spearmanr
      type: spearmanr
      value: 0.8871816808599587
---

<!-- 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. -->

# STSB

This model is a fine-tuned version of [google-t5/t5-base](https://huggingface.co/google-t5/t5-base) on the GLUE STSB dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5496
- Pearson: 0.8882
- Spearmanr: 0.8872
- Combined Score: 0.8877

## 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: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10.0

### Training results

| Training Loss | Epoch | Step | Combined Score | Validation Loss | Pearson | Spearmanr |
|:-------------:|:-----:|:----:|:--------------:|:---------------:|:-------:|:---------:|
| No log        | 1.0   | 180  | 0.8180         | 1.1720          | 0.8128  | 0.8233    |
| No log        | 2.0   | 360  | 0.8588         | 0.7424          | 0.8585  | 0.8591    |
| 1.0195        | 3.0   | 540  | 0.8756         | 0.6313          | 0.8756  | 0.8756    |
| 1.0195        | 4.0   | 720  | 0.8803         | 0.5849          | 0.8801  | 0.8806    |
| 1.0195        | 5.0   | 900  | 0.8833         | 0.6234          | 0.8838  | 0.8827    |
| 0.315         | 6.0   | 1080 | 0.8859         | 0.6469          | 0.8864  | 0.8854    |
| 0.315         | 7.0   | 1260 | 0.8861         | 0.5571          | 0.8866  | 0.8856    |
| 0.315         | 8.0   | 1440 | 0.8869         | 0.5629          | 0.8877  | 0.8862    |
| 0.2087        | 9.0   | 1620 | 0.8877         | 0.5569          | 0.8882  | 0.8871    |
| 0.2087        | 10.0  | 1800 | 0.8877         | 0.5496          | 0.8882  | 0.8872    |


### Framework versions

- Transformers 4.43.3
- Pytorch 1.11.0+cu113
- Datasets 2.20.0
- Tokenizers 0.19.1