|
--- |
|
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: 0.9464516129032258 |
|
--- |
|
|
|
<!-- 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: 0.3038 |
|
- Accuracy: 0.9465 |
|
|
|
## 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 | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| No log | 1.0 | 318 | 2.8460 | 0.7506 | |
|
| 3.322 | 2.0 | 636 | 1.4301 | 0.8532 | |
|
| 3.322 | 3.0 | 954 | 0.7377 | 0.9152 | |
|
| 1.2296 | 4.0 | 1272 | 0.4784 | 0.9316 | |
|
| 0.449 | 5.0 | 1590 | 0.3730 | 0.9390 | |
|
| 0.449 | 6.0 | 1908 | 0.3367 | 0.9429 | |
|
| 0.2424 | 7.0 | 2226 | 0.3163 | 0.9468 | |
|
| 0.1741 | 8.0 | 2544 | 0.3074 | 0.9452 | |
|
| 0.1741 | 9.0 | 2862 | 0.3054 | 0.9458 | |
|
| 0.1501 | 10.0 | 3180 | 0.3038 | 0.9465 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.15.0 |
|
- Pytorch 1.10.0+cu111 |
|
- Datasets 1.17.0 |
|
- Tokenizers 0.10.3 |
|
|
