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:
- accuracy
- f1
tags:
- generated_from_trainer
model-index:
- name: distilbert_sa_GLUE_Experiment_mrpc
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: GLUE MRPC
      type: glue
      config: mrpc
      split: validation
      args: mrpc
    metrics:
    - type: accuracy
      value: 0.696078431372549
      name: Accuracy
    - type: f1
      value: 0.7973856209150327
      name: F1
---

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# distilbert_sa_GLUE_Experiment_mrpc

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the GLUE MRPC dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5911
- Accuracy: 0.6961
- F1: 0.7974
- Combined Score: 0.7467

## 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 | Accuracy | F1     | Combined Score |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
| 0.664         | 1.0   | 15   | 0.6406          | 0.6838   | 0.8122 | 0.7480         |
| 0.6297        | 2.0   | 30   | 0.6118          | 0.6838   | 0.8122 | 0.7480         |
| 0.6048        | 3.0   | 45   | 0.6194          | 0.6765   | 0.7668 | 0.7216         |
| 0.5671        | 4.0   | 60   | 0.5911          | 0.6961   | 0.7974 | 0.7467         |
| 0.4731        | 5.0   | 75   | 0.6775          | 0.6814   | 0.7727 | 0.7270         |
| 0.3304        | 6.0   | 90   | 0.8546          | 0.6225   | 0.7004 | 0.6615         |
| 0.2466        | 7.0   | 105  | 1.0389          | 0.7010   | 0.8039 | 0.7524         |
| 0.1703        | 8.0   | 120  | 1.0860          | 0.6593   | 0.7583 | 0.7088         |
| 0.1328        | 9.0   | 135  | 1.2445          | 0.6397   | 0.7242 | 0.6820         |


### Framework versions

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