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_logit_kd_data_aug_stsb_256
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: GLUE STSB
      type: glue
      args: stsb
    metrics:
    - type: spearmanr
      value: 0.17779903983231324
      name: Spearmanr
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# distilbert_sa_GLUE_Experiment_logit_kd_data_aug_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: 1.4500
- Pearson: 0.1761
- Spearmanr: 0.1778
- Combined Score: 0.1770

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 0.5832        | 1.0   | 1259 | 1.5244          | 0.1737  | 0.1803    | 0.1770         |
| 0.2202        | 2.0   | 2518 | 1.4500          | 0.1761  | 0.1778    | 0.1770         |
| 0.1249        | 3.0   | 3777 | 1.4720          | 0.1743  | 0.1782    | 0.1762         |
| 0.0822        | 4.0   | 5036 | 1.5790          | 0.1581  | 0.1658    | 0.1619         |
| 0.0611        | 5.0   | 6295 | 1.4750          | 0.1850  | 0.1905    | 0.1878         |
| 0.0477        | 6.0   | 7554 | 1.5776          | 0.1612  | 0.1694    | 0.1653         |
| 0.0394        | 7.0   | 8813 | 1.5512          | 0.1648  | 0.1694    | 0.1671         |


### Framework versions

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