README.md

metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - clinc_oos
metrics:
  - accuracy
model-index:
  - name: distilbert-base-uncased-finetuned-clinc
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: clinc_oos
          type: clinc_oos
          args: plus
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.9148387096774193
      - task:
          type: text-classification
          name: Text Classification
        dataset:
          name: clinc_oos
          type: clinc_oos
          config: small
          split: test
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.8627272727272727
            verified: true
          - name: Precision Macro
            type: precision
            value: 0.861664336839455
            verified: true
          - name: Precision Micro
            type: precision
            value: 0.8627272727272727
            verified: true
          - name: Precision Weighted
            type: precision
            value: 0.8787483927993249
            verified: true
          - name: Recall Macro
            type: recall
            value: 0.9187704194260485
            verified: true
          - name: Recall Micro
            type: recall
            value: 0.8627272727272727
            verified: true
          - name: Recall Weighted
            type: recall
            value: 0.8627272727272727
            verified: true
          - name: F1 Macro
            type: f1
            value: 0.8842101413648463
            verified: true
          - name: F1 Micro
            type: f1
            value: 0.8627272727272727
            verified: true
          - name: F1 Weighted
            type: f1
            value: 0.8585620882832584
            verified: true
          - name: loss
            type: loss
            value: 0.9942931532859802
            verified: true

distilbert-base-uncased-finetuned-clinc

This model is a fine-tuned version of distilbert-base-uncased on the clinc_oos dataset. It achieves the following results on the evaluation set:

• Loss: 0.7760
• Accuracy: 0.9148

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: 48
• eval_batch_size: 48
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
4.2994	1.0	318	3.3016	0.7442
2.6387	2.0	636	1.8892	0.8339
1.5535	3.0	954	1.1602	0.8948
1.0139	4.0	1272	0.8619	0.9084
0.7936	5.0	1590	0.7760	0.9148

Framework versions

• Transformers 4.17.0
• Pytorch 1.10.2+cu102
• Datasets 1.18.3
• Tokenizers 0.11.6