transformers tensorboard safetensors distilbert text-classification generated_from_trainer en dataset:glue base_model:gokulsrinivasagan/bert_base_train base_model:finetune:gokulsrinivasagan/bert_base_train license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
base_model: gokulsrinivasagan/bert_base_train
datasets:
- glue
language:
- en
library_name: transformers
license: apache-2.0
metrics:
- spearmanr
tags:
- generated_from_trainer
model-index:
- name: bert_base_train_stsb
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: GLUE STSB
      type: glue
      args: stsb
    metrics:
    - type: spearmanr
      value: 0.518739650924514
      name: Spearmanr
---

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# bert_base_train_stsb

This model is a fine-tuned version of [gokulsrinivasagan/bert_base_train](https://huggingface.co/gokulsrinivasagan/bert_base_train) on the GLUE STSB dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6937
- Pearson: 0.5266
- Spearmanr: 0.5187
- Combined Score: 0.5227

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 2.739         | 1.0   | 23   | 2.3879          | 0.1468  | 0.1339    | 0.1403         |
| 1.8273        | 2.0   | 46   | 1.9865          | 0.3760  | 0.3603    | 0.3682         |
| 1.2961        | 3.0   | 69   | 2.1709          | 0.4475  | 0.4434    | 0.4454         |
| 0.8117        | 4.0   | 92   | 1.9440          | 0.5121  | 0.5227    | 0.5174         |
| 0.5628        | 5.0   | 115  | 1.8854          | 0.5095  | 0.5080    | 0.5087         |
| 0.3981        | 6.0   | 138  | 1.7934          | 0.5146  | 0.5105    | 0.5125         |
| 0.3363        | 7.0   | 161  | 1.7618          | 0.5151  | 0.5137    | 0.5144         |
| 0.253         | 8.0   | 184  | 1.6937          | 0.5266  | 0.5187    | 0.5227         |
| 0.2142        | 9.0   | 207  | 1.7798          | 0.5084  | 0.5013    | 0.5049         |
| 0.1875        | 10.0  | 230  | 1.7994          | 0.5143  | 0.5050    | 0.5097         |
| 0.1705        | 11.0  | 253  | 1.8182          | 0.5105  | 0.5071    | 0.5088         |
| 0.1594        | 12.0  | 276  | 1.8199          | 0.5258  | 0.5222    | 0.5240         |
| 0.1279        | 13.0  | 299  | 1.7347          | 0.5264  | 0.5237    | 0.5250         |


### Framework versions

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