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---
language:
- en
license: mit
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- spearmanr
model-index:
- name: roberta-base-stsb
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE STSB
type: glue
args: stsb
metrics:
- name: Spearmanr
type: spearmanr
value: 0.907904999413384
---
<!-- 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. -->
# roberta-base-stsb
This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the GLUE STSB dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4155
- Pearson: 0.9101
- Spearmanr: 0.9079
- Combined Score: 0.9090
## 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
- lr_scheduler_warmup_ratio: 0.06
- num_epochs: 10.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Pearson | Spearmanr | Combined Score |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| No log | 1.0 | 360 | 0.6202 | 0.8787 | 0.8813 | 0.8800 |
| 1.6425 | 2.0 | 720 | 0.4864 | 0.9008 | 0.8992 | 0.9000 |
| 0.3629 | 3.0 | 1080 | 0.4201 | 0.9043 | 0.9016 | 0.9030 |
| 0.3629 | 4.0 | 1440 | 0.4686 | 0.9052 | 0.9003 | 0.9027 |
| 0.2212 | 5.0 | 1800 | 0.4622 | 0.9061 | 0.9031 | 0.9046 |
| 0.1556 | 6.0 | 2160 | 0.3952 | 0.9086 | 0.9065 | 0.9075 |
| 0.1162 | 7.0 | 2520 | 0.4271 | 0.9081 | 0.9070 | 0.9075 |
| 0.1162 | 8.0 | 2880 | 0.4169 | 0.9094 | 0.9075 | 0.9085 |
| 0.0887 | 9.0 | 3240 | 0.4383 | 0.9091 | 0.9074 | 0.9083 |
| 0.0717 | 10.0 | 3600 | 0.4155 | 0.9101 | 0.9079 | 0.9090 |
### Framework versions
- Transformers 4.20.0.dev0
- Pytorch 1.11.0+cu113
- Datasets 2.1.0
- Tokenizers 0.12.1
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