metadata
license: bsd-3-clause
base_model: MIT/ast-finetuned-audioset-10-10-0.4593
tags:
- generated_from_trainer
metrics:
- accuracy
- recall
- precision
- f1
model-index:
- name: DL_Audio_Hatespeech_ast_trainer_push
results: []
DL_Audio_Hatespeech_ast_trainer_push
This model is a fine-tuned version of MIT/ast-finetuned-audioset-10-10-0.4593 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6336
- Accuracy: 0.6431
- Recall: 0.7452
- Precision: 0.6237
- F1: 0.6790
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: 3e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- 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
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Recall | Precision | F1 |
|---|---|---|---|---|---|---|---|
| 0.6432 | 0.9987 | 387 | 0.6686 | 0.5992 | 0.6580 | 0.5944 | 0.6245 |
| 0.6414 | 2.0 | 775 | 0.6336 | 0.6431 | 0.7452 | 0.6237 | 0.6790 |
| 0.6079 | 2.9987 | 1162 | 0.6505 | 0.6328 | 0.5783 | 0.6561 | 0.6148 |
| 0.5088 | 4.0 | 1550 | 0.7122 | 0.6176 | 0.6624 | 0.6136 | 0.6371 |
| 0.3005 | 4.9935 | 1935 | 0.9250 | 0.6099 | 0.6038 | 0.6176 | 0.6106 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.3.2
- Tokenizers 0.19.1