|
--- |
|
library_name: transformers |
|
license: apache-2.0 |
|
base_model: facebook/wav2vec2-base |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: Wav2Vec2_EmoRecog_Model_v2 |
|
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. --> |
|
|
|
# Wav2Vec2_EmoRecog_Model_v2 |
|
|
|
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the [IEMOCAP](https://sail.usc.edu/iemocap/) dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 1.8440 |
|
- Accuracy: 0.4349 |
|
|
|
## 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: 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: 20 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| 1.7698 | 1.0 | 377 | 1.6608 | 0.3513 | |
|
| 1.6102 | 2.0 | 754 | 1.6074 | 0.3625 | |
|
| 1.5556 | 3.0 | 1131 | 1.5894 | 0.3778 | |
|
| 1.4899 | 4.0 | 1508 | 1.5643 | 0.3858 | |
|
| 1.4322 | 5.0 | 1885 | 1.5250 | 0.4084 | |
|
| 1.3737 | 6.0 | 2262 | 1.5445 | 0.4110 | |
|
| 1.3217 | 7.0 | 2639 | 1.5287 | 0.4210 | |
|
| 1.2686 | 8.0 | 3016 | 1.5635 | 0.4243 | |
|
| 1.1999 | 9.0 | 3393 | 1.5674 | 0.4223 | |
|
| 1.1511 | 10.0 | 3770 | 1.5881 | 0.4363 | |
|
| 1.087 | 11.0 | 4147 | 1.6162 | 0.4177 | |
|
| 1.0309 | 12.0 | 4524 | 1.6487 | 0.4296 | |
|
| 0.9778 | 13.0 | 4901 | 1.7363 | 0.4210 | |
|
| 0.9344 | 14.0 | 5278 | 1.7568 | 0.4210 | |
|
| 0.9108 | 15.0 | 5655 | 1.7051 | 0.4416 | |
|
| 0.8449 | 16.0 | 6032 | 1.7945 | 0.4329 | |
|
| 0.8268 | 17.0 | 6409 | 1.7778 | 0.4402 | |
|
| 0.7991 | 18.0 | 6786 | 1.7972 | 0.4382 | |
|
| 0.7604 | 19.0 | 7163 | 1.8238 | 0.4276 | |
|
| 0.7329 | 20.0 | 7540 | 1.8440 | 0.4349 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.47.1 |
|
- Pytorch 2.5.1+cu121 |
|
- Datasets 3.2.0 |
|
- Tokenizers 0.21.0 |
|
|
