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_logit_kd_stsb
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: GLUE STSB
      type: glue
      config: stsb
      split: validation
      args: stsb
    metrics:
    - type: spearmanr
      value: 0.06502131243296556
      name: Spearmanr
---

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# distilbert_add_GLUE_Experiment_logit_kd_stsb

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: 1.1735
- Pearson: 0.0712
- Spearmanr: 0.0650
- Combined Score: 0.0681

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 1.8584        | 1.0   | 23   | 1.2094          | 0.0666  | 0.0636    | 0.0651         |
| 1.0947        | 2.0   | 46   | 1.2681          | 0.0776  | 0.0622    | 0.0699         |
| 1.0743        | 3.0   | 69   | 1.1735          | 0.0712  | 0.0650    | 0.0681         |
| 1.0098        | 4.0   | 92   | 1.3340          | 0.0809  | 0.0800    | 0.0804         |
| 0.9112        | 5.0   | 115  | 1.2858          | 0.1005  | 0.0958    | 0.0981         |
| 0.8385        | 6.0   | 138  | 1.3734          | 0.1165  | 0.1114    | 0.1140         |
| 0.7601        | 7.0   | 161  | 1.3383          | 0.1358  | 0.1338    | 0.1348         |
| 0.693         | 8.0   | 184  | 1.4171          | 0.1371  | 0.1358    | 0.1365         |


### Framework versions

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