metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- clinc_oos
metrics:
- accuracy
base_model: distilbert-base-uncased
model-index:
- name: distilbert-base-uncased-distilled-clinc
results:
- task:
type: text-classification
name: Text Classification
dataset:
name: clinc_oos
type: clinc_oos
args: plus
metrics:
- type: accuracy
value: 0.9406451612903226
name: Accuracy
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: 0.1002
- Accuracy: 0.9406
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 |
|---|---|---|---|---|
| 0.9039 | 1.0 | 318 | 0.5777 | 0.7335 |
| 0.4486 | 2.0 | 636 | 0.2860 | 0.8768 |
| 0.2528 | 3.0 | 954 | 0.1792 | 0.9210 |
| 0.176 | 4.0 | 1272 | 0.1398 | 0.9274 |
| 0.1417 | 5.0 | 1590 | 0.1209 | 0.9329 |
| 0.1245 | 6.0 | 1908 | 0.1110 | 0.94 |
| 0.1135 | 7.0 | 2226 | 0.1061 | 0.9390 |
| 0.1074 | 8.0 | 2544 | 0.1026 | 0.94 |
| 0.1032 | 9.0 | 2862 | 0.1006 | 0.9410 |
| 0.1017 | 10.0 | 3180 | 0.1002 | 0.9406 |
Framework versions
- Transformers 4.11.3
- Pytorch 1.10.0+cu111
- Datasets 1.16.1
- Tokenizers 0.10.3