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---
library_name: transformers
language:
- en
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- spearmanr
model-index:
- name: bert-base-uncased-finetuned-stsb
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE STSB
type: glue
args: stsb
metrics:
- name: Spearmanr
type: spearmanr
value: 0.8816479546260654
---
<!-- 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-finetuned-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: 0.5010
- Pearson: 0.8856
- Spearmanr: 0.8816
- Combined Score: 0.8836
## 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: 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 1.1212 | 1.0 | 360 | 0.5732 | 0.8790 | 0.8762 | 0.8776 |
| 0.4308 | 2.0 | 720 | 0.5607 | 0.8813 | 0.8777 | 0.8795 |
| 0.2947 | 3.0 | 1080 | 0.5010 | 0.8856 | 0.8816 | 0.8836 |
### Framework versions
- Transformers 4.45.0.dev0
- Pytorch 2.3.0+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1
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