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: train
args: plus
metrics:
- name: Accuracy
type: accuracy
value: 0.9429032258064516
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: 0.1320
- Accuracy: 0.9429
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 |
---|---|---|---|---|
1.1624 | 1.0 | 318 | 0.7529 | 0.7477 |
0.5786 | 2.0 | 636 | 0.3696 | 0.8813 |
0.3163 | 3.0 | 954 | 0.2240 | 0.9194 |
0.211 | 4.0 | 1272 | 0.1742 | 0.9294 |
0.168 | 5.0 | 1590 | 0.1537 | 0.9371 |
0.148 | 6.0 | 1908 | 0.1435 | 0.94 |
0.136 | 7.0 | 2226 | 0.1378 | 0.9397 |
0.1295 | 8.0 | 2544 | 0.1346 | 0.9423 |
0.1251 | 9.0 | 2862 | 0.1325 | 0.9429 |
0.1232 | 10.0 | 3180 | 0.1320 | 0.9429 |
Framework versions
- Transformers 4.22.2
- Pytorch 1.10.0
- Datasets 2.7.1
- Tokenizers 0.12.1