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_sa_GLUE_Experiment_data_aug_stsb_192
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: GLUE STSB
      type: glue
      args: stsb
    metrics:
    - type: spearmanr
      value: 0.18387488801123847
      name: Spearmanr
---

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# distilbert_sa_GLUE_Experiment_data_aug_stsb_192

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: 2.8747
- Pearson: 0.1794
- Spearmanr: 0.1839
- Combined Score: 0.1816

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:---------:|:--------------:|
| 1.2844        | 1.0   | 1259  | 2.8897          | 0.1809  | 0.1879    | 0.1844         |
| 0.4862        | 2.0   | 2518  | 2.9860          | 0.1713  | 0.1773    | 0.1743         |
| 0.3063        | 3.0   | 3777  | 2.8747          | 0.1794  | 0.1839    | 0.1816         |
| 0.2133        | 4.0   | 5036  | 2.9659          | 0.1611  | 0.1665    | 0.1638         |
| 0.1614        | 5.0   | 6295  | 3.0123          | 0.1717  | 0.1793    | 0.1755         |
| 0.1289        | 6.0   | 7554  | 3.0058          | 0.1798  | 0.1900    | 0.1849         |
| 0.1077        | 7.0   | 8813  | 3.0575          | 0.1648  | 0.1786    | 0.1717         |
| 0.0921        | 8.0   | 10072 | 3.0590          | 0.1687  | 0.1758    | 0.1723         |


### Framework versions

- Transformers 4.26.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.9.0
- Tokenizers 0.13.2
