metadata
license: apache-2.0
base_model: distilbert-base-uncased
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
config: plus
split: validation
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: 0.1852
- 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: 0.0004
- train_batch_size: 1280
- eval_batch_size: 1280
- 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 |
|---|---|---|---|---|
| 1.9692 | 1.0 | 12 | 1.3486 | 0.6574 |
| 1.1867 | 2.0 | 24 | 0.5409 | 0.8884 |
| 0.5614 | 3.0 | 36 | 0.2845 | 0.9387 |
| 0.295 | 4.0 | 48 | 0.2234 | 0.9471 |
| 0.1729 | 5.0 | 60 | 0.2021 | 0.9487 |
| 0.1574 | 6.0 | 72 | 0.1942 | 0.9513 |
| 0.1477 | 7.0 | 84 | 0.1895 | 0.9510 |
| 0.1446 | 8.0 | 96 | 0.1870 | 0.9497 |
| 0.1405 | 9.0 | 108 | 0.1856 | 0.9494 |
| 0.1382 | 10.0 | 120 | 0.1852 | 0.9490 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu117
- Datasets 2.14.0
- Tokenizers 0.13.3