metadata

license: apache-2.0
base_model: patnelt60/distilbert-base-uncased-finetuned-clinc
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
          config: plus
          split: validation
          args: plus
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.9267741935483871

distilbert-base-uncased-finetuned-clinc

This model is a fine-tuned version of patnelt60/distilbert-base-uncased-finetuned-clinc on the clinc_oos dataset. It achieves the following results on the evaluation set:

Loss: 0.1904
Accuracy: 0.9268

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: 384
eval_batch_size: 384
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	40	0.4572	0.8619
No log	2.0	80	0.3775	0.8881
No log	3.0	120	0.3184	0.9013
No log	4.0	160	0.2753	0.9110
No log	5.0	200	0.2441	0.9187
No log	6.0	240	0.2224	0.9232
No log	7.0	280	0.2073	0.9248
0.3426	8.0	320	0.1982	0.9268
0.3426	9.0	360	0.1923	0.9265
0.3426	10.0	400	0.1904	0.9268

Framework versions

Transformers 4.32.1
Pytorch 2.1.0
Datasets 2.14.6
Tokenizers 0.13.3