transformers tensorboard safetensors bert text-classification generated_from_trainer en dataset:glue base_model:google/bert_uncased_L-4_H-512_A-8 base_model:finetune:google/bert_uncased_L-4_H-512_A-8 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
base_model: google/bert_uncased_L-4_H-512_A-8
datasets:
- glue
language:
- en
library_name: transformers
license: apache-2.0
metrics:
- spearmanr
tags:
- generated_from_trainer
model-index:
- name: bert_uncased_L-4_H-512_A-8_stsb
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: GLUE STSB
      type: glue
      args: stsb
    metrics:
    - type: spearmanr
      value: 0.8704339623572931
      name: Spearmanr
---

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# bert_uncased_L-4_H-512_A-8_stsb

This model is a fine-tuned version of [google/bert_uncased_L-4_H-512_A-8](https://huggingface.co/google/bert_uncased_L-4_H-512_A-8) on the GLUE STSB dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5646
- Pearson: 0.8739
- Spearmanr: 0.8704
- Combined Score: 0.8721

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 2.5878        | 1.0   | 23   | 0.9754          | 0.7823  | 0.7580    | 0.7702         |
| 0.797         | 2.0   | 46   | 0.7766          | 0.8466  | 0.8482    | 0.8474         |
| 0.5786        | 3.0   | 69   | 0.6314          | 0.8603  | 0.8587    | 0.8595         |
| 0.4961        | 4.0   | 92   | 0.6342          | 0.8643  | 0.8637    | 0.8640         |
| 0.3944        | 5.0   | 115  | 0.6018          | 0.8694  | 0.8683    | 0.8689         |
| 0.3362        | 6.0   | 138  | 0.6101          | 0.8659  | 0.8657    | 0.8658         |
| 0.2932        | 7.0   | 161  | 0.6056          | 0.8678  | 0.8666    | 0.8672         |
| 0.2495        | 8.0   | 184  | 0.6255          | 0.8679  | 0.8672    | 0.8675         |
| 0.2268        | 9.0   | 207  | 0.5970          | 0.8699  | 0.8685    | 0.8692         |
| 0.2037        | 10.0  | 230  | 0.6517          | 0.8691  | 0.8672    | 0.8682         |
| 0.191         | 11.0  | 253  | 0.6017          | 0.8709  | 0.8677    | 0.8693         |
| 0.1678        | 12.0  | 276  | 0.6097          | 0.8704  | 0.8685    | 0.8695         |
| 0.1546        | 13.0  | 299  | 0.6052          | 0.8713  | 0.8701    | 0.8707         |
| 0.1486        | 14.0  | 322  | 0.5914          | 0.8714  | 0.8689    | 0.8701         |
| 0.1372        | 15.0  | 345  | 0.6175          | 0.8738  | 0.8702    | 0.8720         |
| 0.131         | 16.0  | 368  | 0.5826          | 0.8727  | 0.8702    | 0.8715         |
| 0.1216        | 17.0  | 391  | 0.5779          | 0.8717  | 0.8686    | 0.8702         |
| 0.1145        | 18.0  | 414  | 0.5646          | 0.8739  | 0.8704    | 0.8721         |
| 0.1158        | 19.0  | 437  | 0.5811          | 0.8738  | 0.8711    | 0.8724         |
| 0.109         | 20.0  | 460  | 0.5896          | 0.8763  | 0.8720    | 0.8742         |
| 0.105         | 21.0  | 483  | 0.5863          | 0.8737  | 0.8705    | 0.8721         |
| 0.0995        | 22.0  | 506  | 0.5758          | 0.8741  | 0.8701    | 0.8721         |
| 0.0971        | 23.0  | 529  | 0.5781          | 0.8748  | 0.8713    | 0.8731         |


### Framework versions

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