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: 0.9367741935483871
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: 0.4175
- Accuracy: 0.9368
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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 159 | 3.3516 | 0.6652 |
| 3.4274 | 2.0 | 318 | 2.2866 | 0.7848 |
| 3.4274 | 3.0 | 477 | 1.5064 | 0.8545 |
| 1.6307 | 4.0 | 636 | 1.0204 | 0.8971 |
| 1.6307 | 5.0 | 795 | 0.7421 | 0.9177 |
| 0.7641 | 6.0 | 954 | 0.5838 | 0.9258 |
| 0.7641 | 7.0 | 1113 | 0.4986 | 0.9306 |
| 0.4482 | 8.0 | 1272 | 0.4489 | 0.9365 |
| 0.4482 | 9.0 | 1431 | 0.4258 | 0.9368 |
| 0.3442 | 10.0 | 1590 | 0.4175 | 0.9368 |
Framework versions
- Transformers 4.11.3
- Pytorch 1.12.1
- Datasets 1.16.1
- Tokenizers 0.10.3