Hugging Face's logo

autoevaluate
/
binary-classification

Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
Eval Results
Inference Endpoints
Model card Files Metrics Community
127
binary-classification / README.md
lewtun's picture
lewtun HF staff
Add evaluation results on the sst2 config and validation split of glue
a86bae3
preview code
|
raw
history blame
No virus
4.25 kB
metadata
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
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.eyJoYXNoIjoiM2YyZGU5NjQzNGE2ZDAyNzMzMTE5OTA1ZGI3MGZlYTEyOWZkZGMyMzFmOWY2OGMzZDJkNzIwMzViYWFkMGJmNyIsInZlcnNpb24iOjF9.wnq3Nmc_iieKBGDD6Yz4crhORG7Rb5go0DgbUotEQv633amBJkjgAIQL3BvcNQWeMKxsQPomGBxYyhGbxdqxCQ
          - type: precision
            value: 0.8898678414096917
            name: Precision
            verified: true
            verifyToken: >-
              eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMDJlMDA3Mjk3OGY2ZTM1NWRlZGZhMDk5MWY3MDIyOWU5ZjFlY2U0NTBiOTg3YzQzYjljN2Y2MzhkMTI0MWM4YSIsInZlcnNpb24iOjF9.CTkQlCYw7Gd_SXTf8SsUrkjmPbCoA-JzkawIWqLM3o3527KjW6aeD-ZXI5SlfJC-yMFmZXI7b9HbKkICTaSxDQ
          - type: recall
            value: 0.9099099099099099
            name: Recall
            verified: true
            verifyToken: >-
              eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiYTMwOTA5ZWZmNDRhOGFmN2ZmY2M5Njg0ZjUzOWYyZTUyZmNjMTkxMGYxZWQ5YmMxNTg0M2RmOGQ4ZTY4MzJlMiIsInZlcnNpb24iOjF9.bIt71RznYodCLorax-sun6kJkYrp9untPiG4aTKfw_OWXJQmW8tOOkx5a2l230kR0zi64bUnFYdx2jczOxExCQ
          - type: auc
            value: 0.9672186789593331
            name: AUC
            verified: true
            verifyToken: >-
              eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNDllMjM5YWNjMTljNzg0OWRlZGM3YjZlMmRmODg3NDM4MjFjZjllMDE4MzIyYjE0ZTk1MDgyMWVhMGNlODgxZiIsInZlcnNpb24iOjF9.FTqqzim42RGWAy-RgiQ3mGc7DbRGcThJ4TiByh6AjxFsJHUgX2SWqV1LTSTN6WmkYitdiErM28aEhhDhLnD0Bw
          - type: f1
            value: 0.8997772828507795
            name: F1
            verified: true
            verifyToken: >-
              eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiODY3MDc4ODZmODBmMTMyODUzOGQzODg0MjdlNWEyM2ZhNjJjNGY2MWE1Y2IyNDY0ZmI2YjdhNGIxYzJhOWRhNCIsInZlcnNpb24iOjF9.rnPDttnVCjPQsNaD8WQCtyi-AveeLm0M5Xz8gQftq_XOMydPOJuR9h0I-5o-RXfQzGnHFoqzJspqtgJWi2dADA
          - type: loss
            value: 0.30092036724090576
            name: loss
            verified: true
            verifyToken: >-
              eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNjg5ZjU4ZDdlNjc3NzYxNDk5NTYwYjlhZWY4ZjkwMDcwYjliMGI4MmM1MWVlZmJlMWRlZjUxNjA5NTczMTA3NyIsInZlcnNpb24iOjF9.Ayx_RZ_j3iSWm2Lz8YwsKxA4n4BEdwqNqjQGzeKlHOuwDn9tSHgsFiEW4i7EgroNGZWsMqJjrucu1g8s1VU7Cw
          - type: matthews_correlation
            value: 0.793630584795814
            name: matthews_correlation
            verified: true
            verifyToken: >-
              eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMDNhMDc2YjBkNjk5MDY5MDU0NGExMWE0ZDlkZWYxZTczZDY4ZmVlOGE3ZmU0OWNhNmFlYzM3NjQxMWI5MjdhYyIsInZlcnNpb24iOjF9.hoed2rRtuZzXGz7LUGnrqOUL4wm-s_kO-_T3PTCpM5-A4ZtdZzixUl-WCeQRpzOw9wpKOuuD0K06U73lALQyAg

binary-classification

This model is a fine-tuned version of 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