metadata
language:
- en
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- spearmanr
model-index:
- name: hBERTv2_new_pretrain_w_init_48_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: 0.25026626408652064
hBERTv2_new_pretrain_w_init_48_stsb
This model is a fine-tuned version of gokuls/bert_12_layer_model_v2_complete_training_new_wt_init_48 on the GLUE STSB dataset. It achieves the following results on the evaluation set:
- Loss: 2.2569
- Pearson: 0.2426
- Spearmanr: 0.2503
- Combined Score: 0.2465
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: 4e-05
- train_batch_size: 128
- eval_batch_size: 128
- 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
Training results
| Training Loss | Epoch | Step | Validation Loss | Pearson | Spearmanr | Combined Score |
|---|---|---|---|---|---|---|
| 2.3064 | 1.0 | 45 | 2.2784 | 0.1492 | 0.1433 | 0.1462 |
| 1.9454 | 2.0 | 90 | 2.2773 | 0.2660 | 0.2546 | 0.2603 |
| 1.7733 | 3.0 | 135 | 2.2569 | 0.2426 | 0.2503 | 0.2465 |
| 1.4752 | 4.0 | 180 | 2.3395 | 0.2833 | 0.3025 | 0.2929 |
| 1.083 | 5.0 | 225 | 2.4140 | 0.3017 | 0.3066 | 0.3042 |
| 0.8694 | 6.0 | 270 | 2.8854 | 0.2790 | 0.3025 | 0.2908 |
| 0.7272 | 7.0 | 315 | 2.8901 | 0.3041 | 0.3066 | 0.3054 |
| 0.6008 | 8.0 | 360 | 2.6252 | 0.2837 | 0.2833 | 0.2835 |
Framework versions
- Transformers 4.29.2
- Pytorch 1.14.0a0+410ce96
- Datasets 2.12.0
- Tokenizers 0.13.3