| --- |
| license: mit |
| tags: |
| - generated_from_trainer |
| datasets: |
| - clinc_oos |
| metrics: |
| - accuracy |
| model-index: |
| - name: userutterance_classification_verplus |
| 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: 0.9619354838709677 |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # userutterance_classification_verplus |
|
|
| This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the clinc_oos dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.2270 |
| - Accuracy: 0.9619 |
| |
| ## 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: 16 |
| - eval_batch_size: 16 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_steps: 500 |
| - num_epochs: 6 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | 5.0219 | 0.21 | 200 | 4.9813 | 0.0077 | |
| | 4.8915 | 0.42 | 400 | 4.5741 | 0.1155 | |
| | 4.2736 | 0.63 | 600 | 3.5359 | 0.4719 | |
| | 3.2701 | 0.84 | 800 | 2.4291 | 0.7429 | |
| | 2.3578 | 1.05 | 1000 | 1.5793 | 0.8413 | |
| | 1.5695 | 1.26 | 1200 | 1.0029 | 0.8994 | |
| | 1.0412 | 1.47 | 1400 | 0.6475 | 0.9187 | |
| | 0.7034 | 1.68 | 1600 | 0.4439 | 0.9303 | |
| | 0.501 | 1.89 | 1800 | 0.3400 | 0.9381 | |
| | 0.3187 | 2.1 | 2000 | 0.2793 | 0.9439 | |
| | 0.2185 | 2.31 | 2200 | 0.2538 | 0.9490 | |
| | 0.1669 | 2.52 | 2400 | 0.2210 | 0.9523 | |
| | 0.1081 | 2.73 | 2600 | 0.2225 | 0.9519 | |
| | 0.1004 | 2.94 | 2800 | 0.2136 | 0.9555 | |
| | 0.0665 | 3.14 | 3000 | 0.2078 | 0.9561 | |
| | 0.0509 | 3.35 | 3200 | 0.2155 | 0.9568 | |
| | 0.05 | 3.56 | 3400 | 0.2107 | 0.9581 | |
| | 0.0527 | 3.77 | 3600 | 0.2171 | 0.9568 | |
| | 0.0447 | 3.98 | 3800 | 0.2128 | 0.9590 | |
| | 0.0259 | 4.19 | 4000 | 0.2099 | 0.9587 | |
| | 0.0279 | 4.4 | 4200 | 0.2179 | 0.9577 | |
| | 0.0176 | 4.61 | 4400 | 0.2191 | 0.9574 | |
| | 0.0288 | 4.82 | 4600 | 0.2216 | 0.9590 | |
| | 0.0328 | 5.03 | 4800 | 0.2237 | 0.9606 | |
| | 0.0154 | 5.24 | 5000 | 0.2241 | 0.9616 | |
| | 0.0157 | 5.45 | 5200 | 0.2265 | 0.9603 | |
| | 0.023 | 5.66 | 5400 | 0.2276 | 0.9613 | |
| | 0.0178 | 5.87 | 5600 | 0.2270 | 0.9619 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.28.0 |
| - Pytorch 2.0.1+cu118 |
| - Datasets 2.13.1 |
| - Tokenizers 0.13.3 |
|
|
