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
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: GLUE STSB
      type: glue
      config: stsb
      split: validation
      args: stsb
    metrics:
    - type: spearmanr
      value: 0.04469707962921135
      name: Spearmanr
---

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# distilbert_add_GLUE_Experiment_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: 2.2770
- Pearson: 0.0450
- Spearmanr: 0.0447
- Combined Score: 0.0448

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
| 4.11          | 1.0   | 23   | 2.2770          | 0.0450  | 0.0447    | 0.0448         |
| 2.2155        | 2.0   | 46   | 2.4336          | 0.0499  | 0.0451    | 0.0475         |
| 2.1634        | 3.0   | 69   | 2.3207          | 0.0729  | 0.0634    | 0.0681         |
| 2.0618        | 4.0   | 92   | 2.6080          | 0.0787  | 0.0783    | 0.0785         |
| 1.8586        | 5.0   | 115  | 2.4988          | 0.1020  | 0.1017    | 0.1018         |
| 1.6977        | 6.0   | 138  | 2.6166          | 0.1187  | 0.1137    | 0.1162         |


### Framework versions

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