metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- clinc_oos
metrics:
- accuracy
model-index:
- name: distilbert-base-uncased-finetuned-clinc
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: clinc_oos
type: clinc_oos
args: plus
metrics:
- name: Accuracy
type: accuracy
value: 0.853225806451613
distilbert-base-uncased-finetuned-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: 1.7601
- Accuracy: 0.8532
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: 96
- eval_batch_size: 96
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
No log | 1.0 | 159 | 3.9593 | 0.6442 |
4.0539 | 2.0 | 318 | 2.9237 | 0.7606 |
4.0539 | 3.0 | 477 | 2.2412 | 0.8174 |
2.3862 | 4.0 | 636 | 1.8768 | 0.8397 |
2.3862 | 5.0 | 795 | 1.7601 | 0.8532 |
Framework versions
- Transformers 4.11.3
- Pytorch 1.12.1
- Datasets 1.16.1
- Tokenizers 0.10.3