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: 0.9470967741935484
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: 0.2653
- Accuracy: 0.9471
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 | 1.5714 | 0.7371 |
| 1.9106 | 2.0 | 636 | 0.7918 | 0.8655 |
| 1.9106 | 3.0 | 954 | 0.4652 | 0.9110 |
| 0.7184 | 4.0 | 1272 | 0.3420 | 0.9345 |
| 0.3443 | 5.0 | 1590 | 0.3015 | 0.9439 |
| 0.3443 | 6.0 | 1908 | 0.2834 | 0.9442 |
| 0.2513 | 7.0 | 2226 | 0.2732 | 0.9445 |
| 0.2214 | 8.0 | 2544 | 0.2693 | 0.9465 |
| 0.2214 | 9.0 | 2862 | 0.2673 | 0.9452 |
| 0.2117 | 10.0 | 3180 | 0.2653 | 0.9471 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.11.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1