metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - clinc_oos
metrics:
  - accuracy
model-index:
  - name: distilbert-base-uncased-distilled-clinc
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: clinc_oos
          type: clinc_oos
          args: plus
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.9464516129032258
      - task:
          type: text-classification
          name: Text Classification
        dataset:
          name: clinc_oos
          type: clinc_oos
          config: small
          split: test
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.8821818181818182
            verified: true
          - name: Precision Macro
            type: precision
            value: 0.8816826219842071
            verified: true
          - name: Precision Micro
            type: precision
            value: 0.8821818181818182
            verified: true
          - name: Precision Weighted
            type: precision
            value: 0.8968987308324254
            verified: true
          - name: Recall Macro
            type: recall
            value: 0.9481721854304637
            verified: true
          - name: Recall Micro
            type: recall
            value: 0.8821818181818182
            verified: true
          - name: Recall Weighted
            type: recall
            value: 0.8821818181818182
            verified: true
          - name: F1 Macro
            type: f1
            value: 0.9104084366172693
            verified: true
          - name: F1 Micro
            type: f1
            value: 0.8821818181818182
            verified: true
          - name: F1 Weighted
            type: f1
            value: 0.8769424524427132
            verified: true
          - name: loss
            type: loss
            value: 0.5708521604537964
            verified: true

distilbert-base-uncased-distilled-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: 0.3038
Accuracy: 0.9465

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: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	318	2.8460	0.7506
3.322	2.0	636	1.4301	0.8532
3.322	3.0	954	0.7377	0.9152
1.2296	4.0	1272	0.4784	0.9316
0.449	5.0	1590	0.3730	0.9390
0.449	6.0	1908	0.3367	0.9429
0.2424	7.0	2226	0.3163	0.9468
0.1741	8.0	2544	0.3074	0.9452
0.1741	9.0	2862	0.3054	0.9458
0.1501	10.0	3180	0.3038	0.9465

Framework versions

Transformers 4.15.0
Pytorch 1.10.0+cu111
Datasets 1.17.0
Tokenizers 0.10.3