|
--- |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- clinc_oos |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: MiniLMv2-L12-H384-distilled-finetuned-clinc |
|
results: |
|
- task: |
|
name: Text Classification |
|
type: text-classification |
|
dataset: |
|
name: clinc_oos |
|
type: clinc_oos |
|
args: plus |
|
metrics: |
|
- name: Accuracy |
|
type: accuracy |
|
value: 0.9529032258064516 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# MiniLMv2-L12-H384-distilled-finetuned-clinc |
|
|
|
This model is a fine-tuned version of [nreimers/MiniLMv2-L12-H384-distilled-from-RoBERTa-Large](https://huggingface.co/nreimers/MiniLMv2-L12-H384-distilled-from-RoBERTa-Large) on the clinc_oos dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.3058 |
|
- Accuracy: 0.9529 |
|
|
|
## 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: 0.0001 |
|
- train_batch_size: 64 |
|
- eval_batch_size: 64 |
|
- seed: 33 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 10 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| 1.9908 | 1.0 | 239 | 1.6816 | 0.3910 | |
|
| 1.5212 | 2.0 | 478 | 1.2365 | 0.7697 | |
|
| 1.129 | 3.0 | 717 | 0.9209 | 0.8706 | |
|
| 0.8462 | 4.0 | 956 | 0.6978 | 0.9152 | |
|
| 0.6497 | 5.0 | 1195 | 0.5499 | 0.9342 | |
|
| 0.5124 | 6.0 | 1434 | 0.4447 | 0.9445 | |
|
| 0.4196 | 7.0 | 1673 | 0.3797 | 0.9455 | |
|
| 0.3587 | 8.0 | 1912 | 0.3358 | 0.95 | |
|
| 0.3228 | 9.0 | 2151 | 0.3133 | 0.9513 | |
|
| 0.3052 | 10.0 | 2390 | 0.3058 | 0.9529 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.17.0 |
|
- Pytorch 1.10.2+cu113 |
|
- Datasets 1.18.4 |
|
- Tokenizers 0.13.0 |
|
|
