metadata
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- recall
- precision
model-index:
- name: mixed_model_finetuned_cremad
results: []
mixed_model_finetuned_cremad
This model is a fine-tuned version of wav2vec2 on audio stream part and pretrained resnet3d_101 on video stream part , It was trained from scratch on CremaD dataset. This dataset provides 7442 samples of recordings from actors performing on 6 different emotions in English, which are:
emotions = ['angry', 'disgust', 'fearful', 'happy', 'neutral', 'sad']
It achieves the following results on the evaluation set:
- Loss: 0.3098
- Accuracy: 0.8972
- F1: 0.8960
- Recall: 0.8972
- Precision: 0.8974
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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 743
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Recall | Precision |
|---|---|---|---|---|---|---|---|
| 0.7914 | 1.0 | 186 | 1.0595 | 0.7171 | 0.7074 | 0.7171 | 0.7536 |
| 0.5971 | 2.0 | 372 | 0.4401 | 0.8414 | 0.8375 | 0.8414 | 0.8443 |
| 0.2891 | 3.0 | 558 | 0.3863 | 0.8548 | 0.8539 | 0.8548 | 0.8622 |
| 0.1833 | 3.9946 | 743 | 0.3098 | 0.8972 | 0.8960 | 0.8972 | 0.8974 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1