---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: esc50-wav2vec2-base
  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. -->

# esc50-wav2vec2-base

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5005
- Accuracy: 0.765
- F1 Macro: 0.7567

## 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: 8
- eval_batch_size: 8
- seed: 42
- 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
- lr_scheduler_warmup_steps: 225
- num_epochs: 10.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
| 3.7525        | 1.0   | 225  | 3.6525          | 0.21     | 0.1352   |
| 3.2216        | 2.0   | 450  | 3.1632          | 0.315    | 0.2548   |
| 2.7897        | 3.0   | 675  | 2.7468          | 0.465    | 0.4172   |
| 2.3272        | 4.0   | 900  | 2.3903          | 0.575    | 0.5374   |
| 2.0279        | 5.0   | 1125 | 2.1068          | 0.655    | 0.6167   |
| 1.6353        | 6.0   | 1350 | 1.8588          | 0.665    | 0.6386   |
| 1.405         | 7.0   | 1575 | 1.6419          | 0.735    | 0.7068   |
| 1.1893        | 8.0   | 1800 | 1.5005          | 0.765    | 0.7567   |
| 1.0534        | 9.0   | 2025 | 1.4371          | 0.735    | 0.7259   |
| 0.9821        | 10.0  | 2250 | 1.4061          | 0.755    | 0.7381   |


### Framework versions

- Transformers 4.56.1
- Pytorch 2.8.0+cu128
- Datasets 2.19.0
- Tokenizers 0.22.0