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
config: plus
split: validation
args: plus
metrics:
- name: Accuracy
type: accuracy
value: 0.93
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: 0.0355
- Accuracy: 0.93
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 |
|---|---|---|---|---|
| 0.8155 | 1.0 | 318 | 0.4200 | 0.6729 |
| 0.3168 | 2.0 | 636 | 0.1474 | 0.8532 |
| 0.1459 | 3.0 | 954 | 0.0763 | 0.9013 |
| 0.094 | 4.0 | 1272 | 0.0550 | 0.9171 |
| 0.0732 | 5.0 | 1590 | 0.0462 | 0.9226 |
| 0.0635 | 6.0 | 1908 | 0.0413 | 0.93 |
| 0.0573 | 7.0 | 2226 | 0.0387 | 0.9294 |
| 0.0537 | 8.0 | 2544 | 0.0369 | 0.9310 |
| 0.0514 | 9.0 | 2862 | 0.0358 | 0.9319 |
| 0.0504 | 10.0 | 3180 | 0.0355 | 0.93 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3