metadata
license: apache-2.0
base_model: distilbert-base-uncased
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: 0.9490322580645161
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: 0.3032
- Accuracy: 0.9490
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 |
|---|---|---|---|---|
| 2.6314 | 1.0 | 318 | 1.8942 | 0.7274 |
| 1.4611 | 2.0 | 636 | 0.9553 | 0.8594 |
| 0.7635 | 3.0 | 954 | 0.5469 | 0.9181 |
| 0.4613 | 4.0 | 1272 | 0.4035 | 0.9394 |
| 0.3348 | 5.0 | 1590 | 0.3505 | 0.9432 |
| 0.2776 | 6.0 | 1908 | 0.3258 | 0.9445 |
| 0.2509 | 7.0 | 2226 | 0.3148 | 0.9455 |
| 0.236 | 8.0 | 2544 | 0.3066 | 0.9494 |
| 0.2282 | 9.0 | 2862 | 0.3055 | 0.9484 |
| 0.224 | 10.0 | 3180 | 0.3032 | 0.9490 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1
- Datasets 2.12.0
- Tokenizers 0.13.2