|
--- |
|
license: mit |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- snips_built_in_intents |
|
metrics: |
|
- accuracy |
|
base_model: roberta-base |
|
model-index: |
|
- name: roberta-base-finetuned-intent |
|
results: [] |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# roberta-base-finetuned-intent |
|
|
|
This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the snips_built_in_intents dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.2720 |
|
- Accuracy: 0.9333 |
|
|
|
## 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: 1 |
|
- eval_batch_size: 1 |
|
- seed: 42 |
|
- distributed_type: IPU |
|
- gradient_accumulation_steps: 8 |
|
- total_train_batch_size: 8 |
|
- total_eval_batch_size: 5 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 10 |
|
- training precision: Mixed Precision |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| 1.9568 | 1.0 | 37 | 1.7598 | 0.4333 | |
|
| 1.2238 | 2.0 | 74 | 0.8130 | 0.7667 | |
|
| 0.4536 | 3.0 | 111 | 0.4985 | 0.8 | |
|
| 0.2478 | 4.0 | 148 | 0.3535 | 0.8667 | |
|
| 0.0903 | 5.0 | 185 | 0.3110 | 0.8667 | |
|
| 0.0849 | 6.0 | 222 | 0.2720 | 0.9333 | |
|
| 0.0708 | 7.0 | 259 | 0.2742 | 0.8667 | |
|
| 0.0796 | 8.0 | 296 | 0.2839 | 0.8667 | |
|
| 0.0638 | 9.0 | 333 | 0.2949 | 0.8667 | |
|
| 0.0566 | 10.0 | 370 | 0.2925 | 0.8667 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.20.1 |
|
- Pytorch 1.10.0+cpu |
|
- Datasets 2.7.1 |
|
- Tokenizers 0.12.0 |
|
|
