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_384
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: GLUE STSB
      type: glue
      config: stsb
      split: validation
      args: stsb
    metrics:
    - type: spearmanr
      value: 0.0645429363007399
      name: Spearmanr
---

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# distilbert_add_GLUE_Experiment_stsb_384

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: 2.2840
- Pearson: 0.0810
- Spearmanr: 0.0645
- Combined Score: 0.0728

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 4.1199        | 1.0   | 23   | 2.4288          | 0.0129  | 0.0100    | 0.0114         |
| 2.1794        | 2.0   | 46   | 2.3389          | 0.0705  | 0.0708    | 0.0707         |
| 2.1777        | 3.0   | 69   | 2.4374          | 0.0110  | 0.0098    | 0.0104         |
| 2.1687        | 4.0   | 92   | 2.2840          | 0.0810  | 0.0645    | 0.0728         |
| 2.1636        | 5.0   | 115  | 2.3433          | 0.0847  | 0.0760    | 0.0803         |
| 2.0351        | 6.0   | 138  | 2.5863          | 0.0699  | 0.0809    | 0.0754         |
| 1.7847        | 7.0   | 161  | 2.7544          | 0.0920  | 0.1023    | 0.0972         |
| 1.6358        | 8.0   | 184  | 2.8389          | 0.1135  | 0.1197    | 0.1166         |
| 1.5322        | 9.0   | 207  | 2.9114          | 0.1346  | 0.1367    | 0.1356         |


### Framework versions

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