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_pretrain_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: 0.03839834980403017
      name: Spearmanr
---

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# distilbert_add_GLUE_Experiment_logit_kd_pretrain_stsb

This model is a fine-tuned version of [gokuls/distilbert_add_pre-training-complete](https://huggingface.co/gokuls/distilbert_add_pre-training-complete) on the GLUE STSB dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2199
- Pearson: 0.0583
- Spearmanr: 0.0384
- Combined Score: 0.0484

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 1.8784        | 1.0   | 23   | 1.2688          | 0.0461  | 0.0259    | 0.0360         |
| 1.0833        | 2.0   | 46   | 1.3765          | 0.0190  | 0.0161    | 0.0176         |
| 1.0408        | 3.0   | 69   | 1.2379          | 0.0102  | 0.0246    | 0.0174         |
| 1.0289        | 4.0   | 92   | 1.2199          | 0.0583  | 0.0384    | 0.0484         |
| 1.0248        | 5.0   | 115  | 1.3059          | 0.0405  | 0.0470    | 0.0438         |
| 0.99          | 6.0   | 138  | 1.2294          | 0.0822  | 0.0782    | 0.0802         |
| 0.928         | 7.0   | 161  | 1.3883          | 0.1213  | 0.1310    | 0.1261         |
| 0.9014        | 8.0   | 184  | 1.4037          | 0.0892  | 0.1148    | 0.1020         |
| 0.8319        | 9.0   | 207  | 1.2495          | 0.1583  | 0.1653    | 0.1618         |


### Framework versions

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