|
--- |
|
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 |
|
args: plus |
|
metrics: |
|
- name: Accuracy |
|
type: accuracy |
|
value: 0.9332258064516129 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# distilbert-base-uncased-distilled-clinc |
|
|
|
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the clinc_oos dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.1259 |
|
- Accuracy: 0.9332 |
|
|
|
## 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: 7 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| No log | 1.0 | 318 | 0.5952 | 0.7355 | |
|
| 0.7663 | 2.0 | 636 | 0.3130 | 0.8742 | |
|
| 0.7663 | 3.0 | 954 | 0.2024 | 0.9206 | |
|
| 0.3043 | 4.0 | 1272 | 0.1590 | 0.9235 | |
|
| 0.181 | 5.0 | 1590 | 0.1378 | 0.9303 | |
|
| 0.181 | 6.0 | 1908 | 0.1287 | 0.9329 | |
|
| 0.1468 | 7.0 | 2226 | 0.1259 | 0.9332 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.16.2 |
|
- Pytorch 1.10.2+cu102 |
|
- Datasets 1.18.3 |
|
- Tokenizers 0.11.0 |
|
|
