---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- audio-classification
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: wav2vec2-present
  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-present

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the MatsRooth/prosodic_minimal dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1188
- Accuracy: 0.9783

## 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: 4
- eval_batch_size: 4
- seed: 0
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.5859        | 1.0   | 2151  | 0.2952          | 0.9351   |
| 0.4323        | 2.0   | 4302  | 0.2043          | 0.9562   |
| 0.4494        | 3.0   | 6453  | 0.1691          | 0.9644   |
| 0.0351        | 4.0   | 8604  | 0.1447          | 0.9677   |
| 0.2679        | 5.0   | 10755 | 0.1372          | 0.9704   |
| 0.3252        | 6.0   | 12906 | 0.1281          | 0.9720   |
| 0.1319        | 7.0   | 15057 | 0.1087          | 0.9789   |
| 0.0646        | 8.0   | 17208 | 0.1371          | 0.9740   |
| 0.1035        | 9.0   | 19359 | 0.1219          | 0.9776   |
| 0.1148        | 10.0  | 21510 | 0.1188          | 0.9783   |


### Framework versions

- Transformers 4.36.0.dev0
- Pytorch 2.9.0+cu128
- Datasets 2.13.1
- Tokenizers 0.15.0