metadata
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- spearmanr
model-index:
- name: hBERTv2_new_no_pretrain_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: .nan
hBERTv2_new_no_pretrain_stsb
This model is a fine-tuned version of on the glue dataset. It achieves the following results on the evaluation set:
- Loss: 2.2926
- Pearson: nan
- Spearmanr: nan
- Combined Score: nan
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: 0.0005
- 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
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Pearson | Spearmanr | Combined Score |
|---|---|---|---|---|---|---|
| 13.1642 | 1.0 | 45 | 2.2500 | nan | nan | nan |
| 2.3438 | 2.0 | 90 | 2.2500 | -0.0336 | -0.0323 | -0.0329 |
| 2.3125 | 3.0 | 135 | 2.2502 | nan | nan | nan |
| 2.2007 | 4.0 | 180 | 2.3598 | 0.0455 | 0.0438 | 0.0447 |
| 2.2124 | 5.0 | 225 | 2.3019 | nan | nan | nan |
| 2.2073 | 6.0 | 270 | 2.2926 | nan | nan | nan |
Framework versions
- Transformers 4.29.2
- Pytorch 1.14.0a0+410ce96
- Datasets 2.12.0
- Tokenizers 0.13.3