|
--- |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
- precision |
|
- recall |
|
- f1 |
|
model-index: |
|
- name: distilbert-finetuned-gesture-prediction-21-classes |
|
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. --> |
|
|
|
# distilbert-finetuned-gesture-prediction-21-classes |
|
|
|
This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.9212 |
|
- Accuracy: 0.8029 |
|
- Precision: 0.7978 |
|
- Recall: 0.8029 |
|
- F1: 0.7974 |
|
|
|
## 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 |
|
- num_epochs: 10 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
|
| 2.1942 | 1.0 | 104 | 1.3566 | 0.7113 | 0.6581 | 0.7113 | 0.6683 | |
|
| 1.1713 | 2.0 | 208 | 1.0182 | 0.7626 | 0.7445 | 0.7626 | 0.7348 | |
|
| 0.8285 | 3.0 | 312 | 0.9028 | 0.7789 | 0.7626 | 0.7789 | 0.7607 | |
|
| 0.6374 | 4.0 | 416 | 0.8845 | 0.7959 | 0.7950 | 0.7959 | 0.7890 | |
|
| 0.4991 | 5.0 | 520 | 0.8936 | 0.7997 | 0.7949 | 0.7997 | 0.7865 | |
|
| 0.3908 | 6.0 | 624 | 0.8829 | 0.7910 | 0.7879 | 0.7910 | 0.7864 | |
|
| 0.3234 | 7.0 | 728 | 0.9004 | 0.7946 | 0.7898 | 0.7946 | 0.7888 | |
|
| 0.2688 | 8.0 | 832 | 0.8947 | 0.8047 | 0.7993 | 0.8047 | 0.7995 | |
|
| 0.2392 | 9.0 | 936 | 0.9154 | 0.8024 | 0.7980 | 0.8024 | 0.7961 | |
|
| 0.2103 | 10.0 | 1040 | 0.9212 | 0.8029 | 0.7978 | 0.8029 | 0.7974 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.26.1 |
|
- Pytorch 1.13.1+cu116 |
|
- Datasets 2.10.1 |
|
- Tokenizers 0.13.2 |
|
|
