metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- spearmanr
model-index:
- name: distilbert-base-uncased-finetuned-stsb
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: glue
type: glue
config: stsb
split: validation
args: stsb
metrics:
- name: Spearmanr
type: spearmanr
value: 0.8703919468681796
distilbert-base-uncased-finetuned-stsb
This model is a fine-tuned version of distilbert-base-uncased on the glue dataset. It achieves the following results on the evaluation set:
- Loss: 0.5388
- Pearson: 0.8740
- Spearmanr: 0.8704
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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Pearson | Spearmanr |
|---|---|---|---|---|---|
| No log | 1.0 | 360 | 0.6683 | 0.8599 | 0.8575 |
| 1.0348 | 2.0 | 720 | 0.5413 | 0.8715 | 0.8685 |
| 0.3974 | 3.0 | 1080 | 0.5560 | 0.8725 | 0.8692 |
| 0.3974 | 4.0 | 1440 | 0.5666 | 0.8737 | 0.8703 |
| 0.2516 | 5.0 | 1800 | 0.5388 | 0.8740 | 0.8704 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3