metadata
library_name: transformers
license: bsd-3-clause
base_model: MIT/ast-finetuned-audioset-10-10-0.4593
tags:
- generated_from_trainer
metrics:
- accuracy
- recall
- precision
- f1
language:
- en
model-index:
- name: AST_EmoRecog_Model_v3
results: []
AST_EmoRecog_Model_v3
This model is a fine-tuned version of MIT/ast-finetuned-audioset-10-10-0.4593 on the IEMOCAP dataset. It achieves the following results on the evaluation set:
- Loss: 1.2233
- Accuracy: 0.5299
- Recall: 0.3967
- Precision: 0.5460
- F1: 0.3992
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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Recall | Precision | F1 |
|---|---|---|---|---|---|---|---|
| 1.4346 | 1.0 | 377 | 1.2955 | 0.5186 | 0.3738 | 0.5319 | 0.3590 |
| 1.138 | 2.0 | 754 | 1.2554 | 0.5212 | 0.3942 | 0.5089 | 0.3824 |
| 0.9068 | 3.0 | 1131 | 1.2233 | 0.5299 | 0.3967 | 0.5460 | 0.3992 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0