---
library_name: transformers
language:
- en
license: apache-2.0
base_model: google/bert_uncased_L-4_H-256_A-4
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- spearmanr
model-index:
- name: bert_uncased_L-4_H-256_A-4_stsb
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: GLUE STSB
      type: glue
      args: stsb
    metrics:
    - name: Spearmanr
      type: spearmanr
      value: 0.8541619713648296
---

<!-- 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-4_H-256_A-4_stsb

This model is a fine-tuned version of [google/bert_uncased_L-4_H-256_A-4](https://huggingface.co/google/bert_uncased_L-4_H-256_A-4) on the GLUE STSB dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6283
- Pearson: 0.8545
- Spearmanr: 0.8542
- Combined Score: 0.8543

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 5.5773        | 1.0   | 23   | 2.7412          | 0.3845  | 0.3343    | 0.3594         |
| 2.5793        | 2.0   | 46   | 1.9158          | 0.7727  | 0.7557    | 0.7642         |
| 1.5767        | 3.0   | 69   | 0.9541          | 0.7706  | 0.7473    | 0.7590         |
| 0.9474        | 4.0   | 92   | 0.7628          | 0.8133  | 0.8070    | 0.8101         |
| 0.7258        | 5.0   | 115  | 0.6785          | 0.8383  | 0.8429    | 0.8406         |
| 0.6162        | 6.0   | 138  | 0.6756          | 0.8436  | 0.8439    | 0.8437         |
| 0.5455        | 7.0   | 161  | 0.6391          | 0.8480  | 0.8504    | 0.8492         |
| 0.4912        | 8.0   | 184  | 0.6582          | 0.8461  | 0.8472    | 0.8466         |
| 0.4443        | 9.0   | 207  | 0.6561          | 0.8472  | 0.8482    | 0.8477         |
| 0.3995        | 10.0  | 230  | 0.6429          | 0.8504  | 0.8503    | 0.8503         |
| 0.3689        | 11.0  | 253  | 0.6283          | 0.8545  | 0.8542    | 0.8543         |
| 0.3418        | 12.0  | 276  | 0.6592          | 0.8520  | 0.8520    | 0.8520         |
| 0.3302        | 13.0  | 299  | 0.6507          | 0.8524  | 0.8530    | 0.8527         |
| 0.319         | 14.0  | 322  | 0.6484          | 0.8528  | 0.8526    | 0.8527         |
| 0.2863        | 15.0  | 345  | 0.6397          | 0.8526  | 0.8527    | 0.8526         |
| 0.2774        | 16.0  | 368  | 0.6379          | 0.8559  | 0.8555    | 0.8557         |


### Framework versions

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