transformers pytorch tensorboard distilbert text-classification generated_from_trainer en dataset:glue license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
datasets:
- glue
language:
- en
license: apache-2.0
metrics:
- spearmanr
tags:
- generated_from_trainer
model-index:
- name: distilbert_add_GLUE_Experiment_stsb_256
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: GLUE STSB
      type: glue
      config: stsb
      split: validation
      args: stsb
    metrics:
    - type: spearmanr
      value: 0.0744074413403118
      name: Spearmanr
---

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# distilbert_add_GLUE_Experiment_stsb_256

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the GLUE STSB dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2898
- Pearson: 0.0723
- Spearmanr: 0.0744
- Combined Score: 0.0733

## 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
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Pearson | Spearmanr | Combined Score |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 5.798         | 1.0   | 23   | 3.1859          | nan     | nan       | nan            |
| 3.2592        | 2.0   | 46   | 2.3672          | nan     | nan       | nan            |
| 2.3588        | 3.0   | 69   | 2.3366          | nan     | nan       | nan            |
| 2.1815        | 4.0   | 92   | 2.3354          | nan     | nan       | nan            |
| 2.1676        | 5.0   | 115  | 2.3685          | 0.0701  | 0.0628    | 0.0665         |
| 2.1604        | 6.0   | 138  | 2.3425          | 0.0799  | 0.0728    | 0.0764         |
| 2.1203        | 7.0   | 161  | 2.2898          | 0.0723  | 0.0744    | 0.0733         |
| 1.8844        | 8.0   | 184  | 2.7739          | 0.0606  | 0.0839    | 0.0723         |
| 1.7797        | 9.0   | 207  | 2.6237          | 0.0817  | 0.0949    | 0.0883         |
| 1.7003        | 10.0  | 230  | 2.7269          | 0.0957  | 0.1082    | 0.1020         |
| 1.5943        | 11.0  | 253  | 2.6580          | 0.1212  | 0.1276    | 0.1244         |
| 1.5603        | 12.0  | 276  | 2.5384          | 0.1412  | 0.1422    | 0.1417         |


### Framework versions

- Transformers 4.26.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.8.0
- Tokenizers 0.13.2
