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: 0.937741935483871
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: 0.1263
- Accuracy: 0.9377
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: 8
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 318 | 0.7135 | 0.7110 |
| 0.9811 | 2.0 | 636 | 0.3228 | 0.8561 |
| 0.9811 | 3.0 | 954 | 0.1909 | 0.9094 |
| 0.3187 | 4.0 | 1272 | 0.1517 | 0.9261 |
| 0.1735 | 5.0 | 1590 | 0.1379 | 0.9310 |
| 0.1735 | 6.0 | 1908 | 0.1308 | 0.9342 |
| 0.1414 | 7.0 | 2226 | 0.1275 | 0.9368 |
| 0.1306 | 8.0 | 2544 | 0.1263 | 0.9377 |
Framework versions
- Transformers 4.27.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2