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---
language:
- en
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- spearmanr
model-index:
- name: hBERTv1_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: 0.7471924680940966
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# hBERTv1_new_pretrain_w_init_48_stsb
This model is a fine-tuned version of [gokuls/bert_12_layer_model_v1_complete_training_new_wt_init_48](https://huggingface.co/gokuls/bert_12_layer_model_v1_complete_training_new_wt_init_48) on the GLUE STSB dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9800
- Pearson: 0.7515
- Spearmanr: 0.7472
- Combined Score: 0.7493
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 2.5456 | 1.0 | 45 | 2.2706 | 0.1246 | 0.1141 | 0.1194 |
| 2.0514 | 2.0 | 90 | 2.0613 | 0.5266 | 0.5198 | 0.5232 |
| 1.3837 | 3.0 | 135 | 1.1984 | 0.6853 | 0.6942 | 0.6897 |
| 1.0297 | 4.0 | 180 | 1.6176 | 0.6869 | 0.6961 | 0.6915 |
| 0.8064 | 5.0 | 225 | 1.1444 | 0.7476 | 0.7445 | 0.7460 |
| 0.604 | 6.0 | 270 | 1.2754 | 0.7422 | 0.7450 | 0.7436 |
| 0.4818 | 7.0 | 315 | 1.1407 | 0.7687 | 0.7673 | 0.7680 |
| 0.3905 | 8.0 | 360 | 1.1860 | 0.7560 | 0.7604 | 0.7582 |
| 0.3476 | 9.0 | 405 | 0.9800 | 0.7515 | 0.7472 | 0.7493 |
| 0.2819 | 10.0 | 450 | 1.0156 | 0.7521 | 0.7507 | 0.7514 |
| 0.2418 | 11.0 | 495 | 1.0174 | 0.7516 | 0.7480 | 0.7498 |
| 0.2068 | 12.0 | 540 | 1.2367 | 0.7530 | 0.7523 | 0.7527 |
| 0.1863 | 13.0 | 585 | 1.0073 | 0.7491 | 0.7468 | 0.7480 |
| 0.1929 | 14.0 | 630 | 1.0470 | 0.7517 | 0.7505 | 0.7511 |
### Framework versions
- Transformers 4.29.2
- Pytorch 1.14.0a0+410ce96
- Datasets 2.12.0
- Tokenizers 0.13.3
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