metadata
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: 0.9092158650855444
roberta-base-stsb
This model is a fine-tuned version of roberta-base on the GLUE STSB dataset. It achieves the following results on the evaluation set:
- Loss: 0.4221
- Pearson: 0.9116
- Spearmanr: 0.9092
- Combined Score: 0.9104
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 |
|---|---|---|---|---|---|---|
| 1.6552 | 1.39 | 500 | 0.5265 | 0.8925 | 0.8925 | 0.8925 |
| 0.3579 | 2.78 | 1000 | 0.4626 | 0.9022 | 0.8991 | 0.9007 |
| 0.2198 | 4.17 | 1500 | 0.4396 | 0.9054 | 0.9042 | 0.9048 |
| 0.1585 | 5.56 | 2000 | 0.4537 | 0.9069 | 0.9052 | 0.9060 |
| 0.1139 | 6.94 | 2500 | 0.4975 | 0.9091 | 0.9065 | 0.9078 |
| 0.0868 | 8.33 | 3000 | 0.4221 | 0.9116 | 0.9092 | 0.9104 |
| 0.073 | 9.72 | 3500 | 0.4311 | 0.9096 | 0.9077 | 0.9086 |
Framework versions
- Transformers 4.21.3
- Pytorch 1.7.1
- Datasets 1.18.3
- Tokenizers 0.11.6