metadata
language:
- en
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- spearmanr
model-index:
- name: hBERTv2_stsb
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: GLUE STSB
type: glue
config: stsb
split: validation
args: stsb
metrics:
- name: Spearmanr
type: spearmanr
value: 0.7706783096515127
hBERTv2_stsb
This model is a fine-tuned version of gokuls/bert_12_layer_model_v2 on the GLUE STSB dataset. It achieves the following results on the evaluation set:
- Loss: 0.9534
- Pearson: 0.7722
- Spearmanr: 0.7707
- Combined Score: 0.7714
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: 5e-05
- train_batch_size: 256
- eval_batch_size: 256
- seed: 10
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Pearson | Spearmanr | Combined Score |
|---|---|---|---|---|---|---|
| 4.4386 | 1.0 | 23 | 2.5331 | 0.1313 | 0.1071 | 0.1192 |
| 1.8741 | 2.0 | 46 | 2.0517 | 0.4923 | 0.4766 | 0.4844 |
| 1.347 | 3.0 | 69 | 1.3556 | 0.6964 | 0.7079 | 0.7022 |
| 0.8443 | 4.0 | 92 | 1.2583 | 0.7340 | 0.7367 | 0.7353 |
| 0.5822 | 5.0 | 115 | 0.9534 | 0.7722 | 0.7707 | 0.7714 |
| 0.4356 | 6.0 | 138 | 1.1921 | 0.7798 | 0.7771 | 0.7785 |
| 0.3531 | 7.0 | 161 | 1.3849 | 0.7701 | 0.7700 | 0.7700 |
| 0.2712 | 8.0 | 184 | 1.0015 | 0.7886 | 0.7870 | 0.7878 |
| 0.259 | 9.0 | 207 | 1.0523 | 0.7898 | 0.7874 | 0.7886 |
| 0.2003 | 10.0 | 230 | 1.1525 | 0.7836 | 0.7824 | 0.7830 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.14.0a0+410ce96
- Datasets 2.10.1
- Tokenizers 0.13.2