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_96
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: GLUE STSB
      type: glue
      config: stsb
      split: validation
      args: stsb
    metrics:
    - type: spearmanr
      value: .nan
      name: Spearmanr
---

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# distilbert_add_GLUE_Experiment_stsb_96

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: 2.2529
- Pearson: nan
- Spearmanr: nan
- Combined Score: nan

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 8.7243        | 1.0   | 23   | 6.6928          | nan     | nan       | nan            |
| 7.9215        | 2.0   | 46   | 6.2710          | nan     | nan       | nan            |
| 7.4296        | 3.0   | 69   | 5.8601          | nan     | nan       | nan            |
| 6.9483        | 4.0   | 92   | 5.4460          | nan     | nan       | nan            |
| 6.4768        | 5.0   | 115  | 5.0440          | nan     | nan       | nan            |
| 5.9658        | 6.0   | 138  | 4.6523          | nan     | nan       | nan            |
| 5.5067        | 7.0   | 161  | 4.2735          | nan     | nan       | nan            |
| 5.0622        | 8.0   | 184  | 3.9107          | nan     | nan       | nan            |
| 4.6133        | 9.0   | 207  | 3.5725          | nan     | nan       | nan            |
| 4.2011        | 10.0  | 230  | 3.2630          | nan     | nan       | nan            |
| 3.7839        | 11.0  | 253  | 2.9896          | nan     | nan       | nan            |
| 3.4525        | 12.0  | 276  | 2.7549          | 0.0063  | 0.0066    | 0.0064         |
| 3.1246        | 13.0  | 299  | 2.5637          | -0.0161 | -0.0155   | -0.0158        |
| 2.8674        | 14.0  | 322  | 2.4155          | nan     | nan       | nan            |
| 2.6317        | 15.0  | 345  | 2.3138          | nan     | nan       | nan            |
| 2.4623        | 16.0  | 368  | 2.2596          | nan     | nan       | nan            |
| 2.3397        | 17.0  | 391  | 2.2529          | nan     | nan       | nan            |
| 2.2455        | 18.0  | 414  | 2.2910          | nan     | nan       | nan            |
| 2.1984        | 19.0  | 437  | 2.3424          | nan     | nan       | nan            |
| 2.1869        | 20.0  | 460  | 2.3424          | nan     | nan       | nan            |
| 2.1982        | 21.0  | 483  | 2.3460          | nan     | nan       | nan            |
| 2.195         | 22.0  | 506  | 2.3664          | -0.0023 | 0.0002    | -0.0011        |


### Framework versions

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