transformers tensorboard safetensors bert text-classification generated_from_trainer en dataset:glue base_model:google/bert_uncased_L-2_H-512_A-8 base_model:finetune:google/bert_uncased_L-2_H-512_A-8 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
base_model: google/bert_uncased_L-2_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-2_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: 0.8551765830335594
      name: Spearmanr
---

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# bert_uncased_L-2_H-512_A-8_stsb

This model is a fine-tuned version of [google/bert_uncased_L-2_H-512_A-8](https://huggingface.co/google/bert_uncased_L-2_H-512_A-8) on the GLUE STSB dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6358
- Pearson: 0.8581
- Spearmanr: 0.8552
- Combined Score: 0.8566

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 3.6969        | 1.0   | 23   | 1.5140          | 0.7418  | 0.7179    | 0.7298         |
| 1.0774        | 2.0   | 46   | 0.8374          | 0.8224  | 0.8231    | 0.8228         |
| 0.7474        | 3.0   | 69   | 0.6987          | 0.8441  | 0.8408    | 0.8424         |
| 0.6216        | 4.0   | 92   | 0.6728          | 0.8521  | 0.8492    | 0.8507         |
| 0.5299        | 5.0   | 115  | 0.7252          | 0.8542  | 0.8526    | 0.8534         |
| 0.4661        | 6.0   | 138  | 0.6521          | 0.8564  | 0.8543    | 0.8554         |
| 0.4071        | 7.0   | 161  | 0.6358          | 0.8581  | 0.8552    | 0.8566         |
| 0.3604        | 8.0   | 184  | 0.6437          | 0.8567  | 0.8550    | 0.8559         |
| 0.3194        | 9.0   | 207  | 0.6857          | 0.8561  | 0.8530    | 0.8546         |
| 0.2981        | 10.0  | 230  | 0.6473          | 0.8575  | 0.8553    | 0.8564         |
| 0.2647        | 11.0  | 253  | 0.6541          | 0.8586  | 0.8552    | 0.8569         |
| 0.244         | 12.0  | 276  | 0.6888          | 0.8572  | 0.8546    | 0.8559         |


### Framework versions

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