transformers pytorch tensorboard distilbert text-classification generated_from_trainer dataset:glue license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
datasets:
- glue
license: apache-2.0
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: autoevaluate-binary-classification
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: glue
      type: glue
      args: sst2
    metrics:
    - type: accuracy
      value: 0.8967889908256881
      name: Accuracy
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: glue
      type: glue
      config: sst2
      split: validation
    metrics:
    - type: accuracy
      value: 0.8967889908256881
      name: Accuracy
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNTZmNGE1N2FjODM3OGJiM2Q2NTY5MzZjNGFhNGVjYzcwOTlkMzVhYjdmOTgwY2Y1NzMyZjY0NzAxMzZkMjM4NyIsInZlcnNpb24iOjF9.LabPe-QWLUUJdPyQ0Ki9rHq74opfAO1fxvu2FjUFiY9zhxAe0RKNjZRHPbrF10249Z3kDZSAq2yzQ1TjKvoLBQ
    - type: precision
      value: 0.8898678414096917
      name: Precision
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMTczZjUwY2MzNTMzY2VlMjFmZGI2MzAwNTEwM2IzYWVkYmFiNjk0MDM3YmYzYjFmNGM3NWI5NDIzODJjMTA1ZCIsInZlcnNpb24iOjF9.3RC343Rtep7yxGH82c1WV2IAVqhJTRoOwiwFVp_w0K0JK_dTqnfEylLb1yMt367ztvkhhOgRn4i9GsL4ZNC5BQ
    - type: recall
      value: 0.9099099099099099
      name: Recall
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNmM4M2Y3YTVjOTlhZjc2OGUxMzFhNGI3YzM4MDI0NDMwMmQyMmRmY2MyMTI5ZTdmYWVjMTlmYWE0N2Q0ZjJiNyIsInZlcnNpb24iOjF9.lMKosw258_E40HdqY8BFyWVJYAMx4cpVyYusGEqN429_cv3DzeIMaOr00trGsJX3BIqr-j5ScjLVV79f5nK2CA
    - type: auc
      value: 0.9672186789593331
      name: AUC
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMzY1YmM4YjJhNTY2ZmIyYmI5ZTBjZjc3MDZiMzQ3ZTEyZWQ1M2I4ZTk4OGYwNzZiY2VlODRkODRjNTg2MDNmMSIsInZlcnNpb24iOjF9.tO3GQ5Rgl26zHz18-yR2wtcajmb_MEPNCZiA1Exz4255-m1iDFyMPM2Pw4s75xUSXWzsF--bo6eqmCLo4yjkBw
    - type: f1
      value: 0.8997772828507795
      name: F1
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMmM0ZjhjZWY2ZGZiYWZhOTY2OWUwNzcxMTRlNjU4MDMyMWViMjg2YzE0YzBiMzVlYTU2ODkyZWY0MzcxOWJlOCIsInZlcnNpb24iOjF9.sySuyn4j72Gt3wstru118StL7pzGgZKzAPtE0FM7HVfdBrVXwZckKaUmoQR-nKaVynbo1h4mykNdM-_MwmLlCA
    - type: loss
      value: 0.30092036724090576
      name: loss
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNDQ2ZjJiMjVhNTMxZGIxMTFlMjVhYTQyOGI2YjgyOTI3OTQ4NGU0ZWYxMDY2MmI1OGNiNDcwNTU3MmEzM2YzZSIsInZlcnNpb24iOjF9.MGCrOvwyOdMQ91z2pzgsIxS-PMCZy2YwNX7IuMNAVokRhTSGUYtFt-8px1Dv9w39IT6ZbySZ7kQQKz6kK8HWAQ
    - type: matthews_correlation
      value: 0.793630584795814
      name: matthews_correlation
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiOGY5ODMyZjc4MTk0NWU1YTRmNGI5NDU0ZGRlMDEwY2ZhN2YzMjAxNDE2MTY4ZTI2OWZjMzkwMzc5NTY3NTlkMSIsInZlcnNpb24iOjF9.1WB_1AIkuk68pphfqpqB_T1VpM3wJPe7mNGOvaDANcek7TKUFuT6kA8J1h1SICS_80mdXDI4yJGGZy3CZwpXDQ
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# binary-classification

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the glue dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3009
- Accuracy: 0.8968

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.175         | 1.0   | 4210 | 0.3009          | 0.8968   |


### Framework versions

- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1
