README.md

metadata

license: mit
tags:
  - generated_from_trainer
datasets:
  - clinc_oos
metrics:
  - accuracy
model-index:
  - name: roberta-large-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: 0.9729032258064516
      - task:
          type: text-classification
          name: Text Classification
        dataset:
          name: clinc_oos
          type: clinc_oos
          config: small
          split: test
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.9143636363636364
            verified: true
          - name: Precision Macro
            type: precision
            value: 0.9124454620291447
            verified: true
          - name: Precision Micro
            type: precision
            value: 0.9143636363636364
            verified: true
          - name: Precision Weighted
            type: precision
            value: 0.9252546056457686
            verified: true
          - name: Recall Macro
            type: recall
            value: 0.9688300220750551
            verified: true
          - name: Recall Micro
            type: recall
            value: 0.9143636363636364
            verified: true
          - name: Recall Weighted
            type: recall
            value: 0.9143636363636364
            verified: true
          - name: F1 Macro
            type: f1
            value: 0.9373460559084424
            verified: true
          - name: F1 Micro
            type: f1
            value: 0.9143636363636364
            verified: true
          - name: F1 Weighted
            type: f1
            value: 0.9114334945621075
            verified: true
          - name: loss
            type: loss
            value: 0.48012402653694153
            verified: true

roberta-large-finetuned-clinc

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

• Loss: 0.1574
• Accuracy: 0.9729

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: 64
• eval_batch_size: 64
• 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
No log	1.0	239	0.8113	0.9035
No log	2.0	478	0.2364	0.9548
1.7328	3.0	717	0.1760	0.9684
1.7328	4.0	956	0.1565	0.9723
0.0976	5.0	1195	0.1574	0.9729

Framework versions

• Transformers 4.11.3
• Pytorch 1.11.0
• Datasets 1.16.1
• Tokenizers 0.10.3