---
library_name: transformers
language:
- en
license: apache-2.0
base_model: google/bert_uncased_L-2_H-128_A-2
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- spearmanr
model-index:
- name: bert_uncased_L-2_H-128_A-2_stsb
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE STSB
      type: glue
      args: stsb
    metrics:
    - name: Spearmanr
      type: spearmanr
      value: 0.8077953690447974
---

<!-- 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. -->

# bert_uncased_L-2_H-128_A-2_stsb

This model is a fine-tuned version of [google/bert_uncased_L-2_H-128_A-2](https://huggingface.co/google/bert_uncased_L-2_H-128_A-2) on the GLUE STSB dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9185
- Pearson: 0.7914
- Spearmanr: 0.8078
- Combined Score: 0.7996

## 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
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Pearson | Spearmanr | Combined Score |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 8.7461        | 1.0   | 23   | 5.9052          | 0.2839  | 0.2249    | 0.2544         |
| 6.3503        | 2.0   | 46   | 4.1500          | 0.4510  | 0.3995    | 0.4253         |
| 4.6275        | 3.0   | 69   | 3.1621          | 0.5516  | 0.5407    | 0.5462         |
| 3.6391        | 4.0   | 92   | 2.6588          | 0.6168  | 0.6455    | 0.6311         |
| 3.0189        | 5.0   | 115  | 2.3421          | 0.6722  | 0.7192    | 0.6957         |
| 2.59          | 6.0   | 138  | 2.0467          | 0.6785  | 0.7346    | 0.7066         |
| 2.172         | 7.0   | 161  | 1.6885          | 0.6686  | 0.6274    | 0.6480         |
| 1.7948        | 8.0   | 184  | 1.4313          | 0.6900  | 0.6565    | 0.6733         |
| 1.5153        | 9.0   | 207  | 1.2854          | 0.7049  | 0.7020    | 0.7035         |
| 1.3213        | 10.0  | 230  | 1.1953          | 0.7136  | 0.7304    | 0.7220         |
| 1.1482        | 11.0  | 253  | 1.1937          | 0.7066  | 0.7005    | 0.7035         |
| 1.0318        | 12.0  | 276  | 1.0680          | 0.7379  | 0.7727    | 0.7553         |
| 0.9444        | 13.0  | 299  | 1.0875          | 0.7445  | 0.7877    | 0.7661         |
| 0.8957        | 14.0  | 322  | 1.0566          | 0.7515  | 0.7869    | 0.7692         |
| 0.8101        | 15.0  | 345  | 1.0417          | 0.7613  | 0.7947    | 0.7780         |
| 0.7743        | 16.0  | 368  | 0.9960          | 0.7708  | 0.7945    | 0.7827         |
| 0.7407        | 17.0  | 391  | 0.9344          | 0.7847  | 0.8062    | 0.7954         |
| 0.6842        | 18.0  | 414  | 0.9185          | 0.7914  | 0.8078    | 0.7996         |
| 0.6628        | 19.0  | 437  | 0.9989          | 0.7836  | 0.7979    | 0.7907         |
| 0.6402        | 20.0  | 460  | 0.9199          | 0.7952  | 0.8082    | 0.8017         |
| 0.6215        | 21.0  | 483  | 0.9276          | 0.7954  | 0.8100    | 0.8027         |
| 0.6069        | 22.0  | 506  | 0.9503          | 0.7956  | 0.8078    | 0.8017         |
| 0.6101        | 23.0  | 529  | 0.9789          | 0.7972  | 0.8134    | 0.8053         |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.2.1+cu118
- Datasets 2.17.0
- Tokenizers 0.20.3