transformers pytorch tensorboard hybridbert text-classification generated_from_trainer en dataset:glue model-index autotrain_compatible endpoints_compatible region:us
---
datasets:
- glue
language:
- en
metrics:
- spearmanr
tags:
- generated_from_trainer
model-index:
- name: hBERTv1_new_pretrain_48_KD_w_init_stsb
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: GLUE STSB
      type: glue
      config: stsb
      split: validation
      args: stsb
    metrics:
    - type: spearmanr
      value: 0.10998236405846894
      name: Spearmanr
---

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# hBERTv1_new_pretrain_48_KD_w_init_stsb

This model is a fine-tuned version of [gokuls/bert_12_layer_model_v1_complete_training_new_48_KD_wt_init](https://huggingface.co/gokuls/bert_12_layer_model_v1_complete_training_new_48_KD_wt_init) on the GLUE STSB dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3593
- Pearson: 0.1283
- Spearmanr: 0.1100
- Combined Score: 0.1192

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 2.3304        | 1.0   | 45   | 2.3593          | 0.1283  | 0.1100    | 0.1192         |
| 1.9951        | 2.0   | 90   | 2.5865          | 0.1746  | 0.1639    | 0.1692         |
| 1.8698        | 3.0   | 135  | 2.4068          | 0.1900  | 0.1928    | 0.1914         |
| 1.535         | 4.0   | 180  | 2.4625          | 0.2815  | 0.2884    | 0.2849         |
| 1.1788        | 5.0   | 225  | 2.6830          | 0.3003  | 0.2981    | 0.2992         |
| 0.8586        | 6.0   | 270  | 2.5719          | 0.3295  | 0.3452    | 0.3373         |


### Framework versions

- Transformers 4.30.2
- Pytorch 1.14.0a0+410ce96
- Datasets 2.13.0
- Tokenizers 0.13.3
