metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- clinc_oos
metrics:
- accuracy
base_model: distilbert-base-uncased
model-index:
- name: distilbert-base-uncased-distilled-clinc
results:
- task:
type: text-classification
name: Text Classification
dataset:
name: clinc_oos
type: clinc_oos
args: plus
metrics:
- type: accuracy
value: 0.9309677419354838
name: Accuracy
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: 0.0389
- Accuracy: 0.9310
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 |
|---|---|---|---|---|
| 0.6206 | 1.0 | 318 | 0.3251 | 0.6610 |
| 0.2571 | 2.0 | 636 | 0.1366 | 0.8584 |
| 0.1392 | 3.0 | 954 | 0.0813 | 0.9081 |
| 0.0967 | 4.0 | 1272 | 0.0598 | 0.9152 |
| 0.0779 | 5.0 | 1590 | 0.0503 | 0.9229 |
| 0.0675 | 6.0 | 1908 | 0.0451 | 0.9271 |
| 0.0615 | 7.0 | 2226 | 0.0425 | 0.9326 |
| 0.058 | 8.0 | 2544 | 0.0403 | 0.9316 |
| 0.0557 | 9.0 | 2862 | 0.0393 | 0.9306 |
| 0.0544 | 10.0 | 3180 | 0.0389 | 0.9310 |
Framework versions
- Transformers 4.19.3
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1