---
library_name: transformers
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: wav2vec-bert-ser-standard
  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. -->

# wav2vec-bert-ser-standard

This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3597
- F1: 0.5549
- Accuracy: 0.564

## 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: 8
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:--------:|
| 30.8905       | 1.0   | 16   | 3.6367          | 0.1464 | 0.24     |
| 28.7614       | 2.0   | 32   | 3.5061          | 0.1679 | 0.256    |
| 27.0469       | 3.0   | 48   | 3.3160          | 0.3390 | 0.388    |
| 27.3445       | 4.0   | 64   | 3.0776          | 0.3525 | 0.396    |
| 24.3884       | 5.0   | 80   | 2.9147          | 0.4089 | 0.452    |
| 24.4721       | 6.0   | 96   | 2.7240          | 0.4445 | 0.472    |
| 22.5651       | 7.0   | 112  | 2.6093          | 0.5077 | 0.532    |
| 21.9695       | 8.0   | 128  | 2.6026          | 0.4392 | 0.476    |
| 21.3548       | 9.0   | 144  | 2.3849          | 0.5656 | 0.584    |
| 18.9157       | 10.0  | 160  | 2.3597          | 0.5549 | 0.564    |


### Framework versions

- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.8.3
- Tokenizers 0.22.2