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: 0.9474193548387096
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: 0.2454
- Accuracy: 0.9474
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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 3.496 | 1.0 | 954 | 1.8019 | 0.8306 |
| 1.0663 | 2.0 | 1908 | 0.5690 | 0.9174 |
| 0.3267 | 3.0 | 2862 | 0.3128 | 0.9406 |
| 0.1397 | 4.0 | 3816 | 0.2567 | 0.9445 |
| 0.0846 | 5.0 | 4770 | 0.2454 | 0.9474 |
Framework versions
- Transformers 4.19.2
- Pytorch 1.11.0
- Datasets 1.16.1
- Tokenizers 0.12.1