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---
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
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