metadata
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distilbert-finetuned-gesture-prediction-9-classes
results: []
distilbert-finetuned-gesture-prediction-9-classes
This model is a fine-tuned version of distilbert-base-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6777
- Precision: 0.6010
- Recall: 0.7343
- F1: 0.6610
- Accuracy: 0.8377
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: 8.095835821517118e-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: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 1.163 | 1.0 | 87 | 0.7279 | 0.4693 | 0.6350 | 0.5397 | 0.8008 |
| 0.5038 | 2.0 | 174 | 0.6673 | 0.6132 | 0.7197 | 0.6622 | 0.8291 |
| 0.2876 | 3.0 | 261 | 0.6539 | 0.5954 | 0.7241 | 0.6535 | 0.8340 |
| 0.1449 | 4.0 | 348 | 0.6777 | 0.6010 | 0.7343 | 0.6610 | 0.8377 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2