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: 0.9490322580645161
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: 0.2396
- Accuracy: 0.9490
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 |
|---|---|---|---|---|
| 2.4105 | 1.0 | 318 | 1.7674 | 0.7568 |
| 1.3717 | 2.0 | 636 | 0.9207 | 0.8716 |
| 0.7351 | 3.0 | 954 | 0.5276 | 0.9197 |
| 0.4354 | 4.0 | 1272 | 0.3646 | 0.9377 |
| 0.2955 | 5.0 | 1590 | 0.2968 | 0.9439 |
| 0.231 | 6.0 | 1908 | 0.2671 | 0.9477 |
| 0.198 | 7.0 | 2226 | 0.2513 | 0.9490 |
| 0.1802 | 8.0 | 2544 | 0.2446 | 0.9484 |
| 0.1707 | 9.0 | 2862 | 0.2416 | 0.9490 |
| 0.1671 | 10.0 | 3180 | 0.2396 | 0.9490 |
Framework versions
- Transformers 4.16.2
- Pytorch 2.0.1+cu118
- Datasets 1.16.1
- Tokenizers 0.13.3