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---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- spearmanr
base_model: bert-base-uncased
model-index:
- name: bert-base-uncased-stsb
results:
- task:
type: text-classification
name: Text Classification
dataset:
name: GLUE STSB
type: glue
args: stsb
metrics:
- type: spearmanr
value: 0.8843169724798454
name: Spearmanr
---
<!-- 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. -->
# bert-base-uncased-stsb
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the GLUE STSB dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5144
- Pearson: 0.8875
- Spearmanr: 0.8843
- Combined Score: 0.8859
## 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: 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: 3.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Pearson | Spearmanr | Combined Score |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| No log | 1.0 | 180 | 0.5179 | 0.8806 | 0.8735 | 0.8771 |
| No log | 2.0 | 360 | 0.5145 | 0.8850 | 0.8820 | 0.8835 |
| 0.7868 | 3.0 | 540 | 0.5144 | 0.8875 | 0.8843 | 0.8859 |
### Framework versions
- Transformers 4.20.0.dev0
- Pytorch 1.11.0+cu113
- Datasets 2.1.0
- Tokenizers 0.12.1
|