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: 0.9390322580645162
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: 0.0990
- Accuracy: 0.9390
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 |
|---|---|---|---|---|
| 1.0901 | 1.0 | 318 | 0.6293 | 0.7026 |
| 0.4796 | 2.0 | 636 | 0.2666 | 0.8661 |
| 0.2386 | 3.0 | 954 | 0.1553 | 0.9148 |
| 0.1591 | 4.0 | 1272 | 0.1238 | 0.9271 |
| 0.1309 | 5.0 | 1590 | 0.1121 | 0.9339 |
| 0.118 | 6.0 | 1908 | 0.1065 | 0.9371 |
| 0.11 | 7.0 | 2226 | 0.1033 | 0.9394 |
| 0.1057 | 8.0 | 2544 | 0.1002 | 0.9377 |
| 0.1032 | 9.0 | 2862 | 0.0995 | 0.9384 |
| 0.1014 | 10.0 | 3180 | 0.0990 | 0.9390 |
Framework versions
- Transformers 4.11.3
- Pytorch 1.12.0+cu113
- Datasets 1.16.1
- Tokenizers 0.10.3