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: 0.9432258064516129
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: 0.1770
- Accuracy: 0.9432
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 |
|---|---|---|---|---|
| 1.5226 | 1.0 | 318 | 0.9867 | 0.7287 |
| 0.76 | 2.0 | 636 | 0.4736 | 0.8561 |
| 0.3972 | 3.0 | 954 | 0.2794 | 0.9126 |
| 0.2541 | 4.0 | 1272 | 0.2189 | 0.9294 |
| 0.2017 | 5.0 | 1590 | 0.1971 | 0.9361 |
| 0.1805 | 6.0 | 1908 | 0.1880 | 0.9406 |
| 0.1685 | 7.0 | 2226 | 0.1826 | 0.9413 |
| 0.1626 | 8.0 | 2544 | 0.1799 | 0.9426 |
| 0.1589 | 9.0 | 2862 | 0.1782 | 0.9429 |
| 0.1569 | 10.0 | 3180 | 0.1770 | 0.9432 |
Framework versions
- Transformers 4.11.3
- Pytorch 1.9.1+cu102
- Datasets 1.13.0
- Tokenizers 0.10.3