metadata
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
bert-base-uncased-finetuned-stsb
This model is a fine-tuned version of 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