transformers tensorboard safetensors bert text-classification generated_from_trainer en dataset:glue base_model:google/bert_uncased_L-4_H-128_A-2 base_model:finetune:google/bert_uncased_L-4_H-128_A-2 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
base_model: google/bert_uncased_L-4_H-128_A-2
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-128_A-2_stsb
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: GLUE STSB
      type: glue
      args: stsb
    metrics:
    - type: spearmanr
      value: 0.827487669005796
      name: Spearmanr
---

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# bert_uncased_L-4_H-128_A-2_stsb

This model is a fine-tuned version of [google/bert_uncased_L-4_H-128_A-2](https://huggingface.co/google/bert_uncased_L-4_H-128_A-2) on the GLUE STSB dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7195
- Pearson: 0.8255
- Spearmanr: 0.8275
- Combined Score: 0.8265

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 6.5937        | 1.0   | 23   | 4.2841          | 0.1711  | 0.2041    | 0.1876         |
| 4.7932        | 2.0   | 46   | 3.4947          | 0.2599  | 0.2547    | 0.2573         |
| 3.9815        | 3.0   | 69   | 2.9842          | 0.1082  | 0.1081    | 0.1081         |
| 3.3791        | 4.0   | 92   | 2.6163          | 0.0598  | 0.0576    | 0.0587         |
| 2.8814        | 5.0   | 115  | 2.3940          | nan     | nan       | nan            |
| 2.5786        | 6.0   | 138  | 2.2811          | nan     | nan       | nan            |
| 2.3519        | 7.0   | 161  | 2.2501          | nan     | nan       | nan            |
| 2.2133        | 8.0   | 184  | 2.2792          | 0.3315  | 0.3276    | 0.3295         |
| 2.0732        | 9.0   | 207  | 1.7190          | 0.6363  | 0.5993    | 0.6178         |
| 1.688         | 10.0  | 230  | 1.2774          | 0.7001  | 0.7069    | 0.7035         |
| 1.3697        | 11.0  | 253  | 1.2016          | 0.6980  | 0.7378    | 0.7179         |
| 1.197         | 12.0  | 276  | 1.1024          | 0.7279  | 0.7207    | 0.7243         |
| 1.0723        | 13.0  | 299  | 0.9007          | 0.7777  | 0.7922    | 0.7849         |
| 0.9748        | 14.0  | 322  | 0.8908          | 0.7814  | 0.7975    | 0.7895         |
| 0.923         | 15.0  | 345  | 0.8621          | 0.7905  | 0.8112    | 0.8008         |
| 0.8518        | 16.0  | 368  | 0.8973          | 0.7831  | 0.7829    | 0.7830         |
| 0.7957        | 17.0  | 391  | 0.7932          | 0.8057  | 0.8142    | 0.8100         |
| 0.7691        | 18.0  | 414  | 0.8001          | 0.8066  | 0.8182    | 0.8124         |
| 0.7204        | 19.0  | 437  | 0.7710          | 0.8134  | 0.8204    | 0.8169         |
| 0.6959        | 20.0  | 460  | 0.7704          | 0.8145  | 0.8228    | 0.8187         |
| 0.6458        | 21.0  | 483  | 0.7613          | 0.8175  | 0.8231    | 0.8203         |
| 0.6427        | 22.0  | 506  | 0.7614          | 0.8188  | 0.8233    | 0.8210         |
| 0.6307        | 23.0  | 529  | 0.7195          | 0.8255  | 0.8275    | 0.8265         |
| 0.5979        | 24.0  | 552  | 0.7540          | 0.8207  | 0.8243    | 0.8225         |
| 0.5774        | 25.0  | 575  | 0.7823          | 0.8183  | 0.8226    | 0.8204         |
| 0.5542        | 26.0  | 598  | 0.7305          | 0.8253  | 0.8278    | 0.8266         |
| 0.548         | 27.0  | 621  | 0.7279          | 0.8261  | 0.8278    | 0.8270         |
| 0.5295        | 28.0  | 644  | 0.7397          | 0.8254  | 0.8267    | 0.8260         |


### Framework versions

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