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_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_sa_GLUE_Experiment_logit_kd_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: 1.1255
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 4.2655        | 1.0   | 23   | 3.2719          | 0.0074  | 0.0048    | 0.0061         |
| 3.8876        | 2.0   | 46   | 3.0839          | -0.0416 | -0.0423   | -0.0420        |
| 3.6577        | 3.0   | 69   | 2.8849          | nan     | nan       | nan            |
| 3.4237        | 4.0   | 92   | 2.6822          | 0.0011  | 0.0035    | 0.0023         |
| 3.1879        | 5.0   | 115  | 2.4766          | nan     | nan       | nan            |
| 2.9317        | 6.0   | 138  | 2.2745          | 0.0091  | 0.0098    | 0.0094         |
| 2.6928        | 7.0   | 161  | 2.0801          | 0.0173  | 0.0165    | 0.0169         |
| 2.4619        | 8.0   | 184  | 1.8985          | -0.0019 | -0.0026   | -0.0023        |
| 2.2395        | 9.0   | 207  | 1.7302          | nan     | nan       | nan            |
| 2.0254        | 10.0  | 230  | 1.5798          | nan     | nan       | nan            |
| 1.8258        | 11.0  | 253  | 1.4485          | nan     | nan       | nan            |
| 1.6552        | 12.0  | 276  | 1.3382          | -0.0040 | -0.0043   | -0.0041        |
| 1.511         | 13.0  | 299  | 1.2493          | -0.0376 | -0.0378   | -0.0377        |
| 1.3781        | 14.0  | 322  | 1.1843          | nan     | nan       | nan            |
| 1.2754        | 15.0  | 345  | 1.1427          | nan     | nan       | nan            |
| 1.193         | 16.0  | 368  | 1.1255          | nan     | nan       | nan            |
| 1.1427        | 17.0  | 391  | 1.1320          | 0.0123  | 0.0102    | 0.0113         |
| 1.1061        | 18.0  | 414  | 1.1565          | 0.0412  | 0.0370    | 0.0391         |
| 1.0979        | 19.0  | 437  | 1.1724          | nan     | nan       | nan            |
| 1.0972        | 20.0  | 460  | 1.1748          | 0.0246  | 0.0255    | 0.0251         |
| 1.0882        | 21.0  | 483  | 1.1792          | nan     | nan       | nan            |


### Framework versions

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