---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Wav2Vec2_Finetuned
  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_Finetuned

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: 0.9886
- Accuracy: 0.7247

## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- 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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 2.1066        | 0.9863 | 54   | 2.0550          | 0.3211   |
| 1.7945        | 1.9817 | 108  | 1.8463          | 0.3858   |
| 1.5042        | 2.9772 | 162  | 1.6106          | 0.4911   |
| 1.3307        | 3.9909 | 217  | 1.3656          | 0.6199   |
| 1.1295        | 4.9863 | 271  | 1.2506          | 0.6417   |
| 1.0127        | 5.9817 | 325  | 1.2754          | 0.6211   |
| 0.949         | 6.9772 | 379  | 1.0925          | 0.7041   |
| 0.8618        | 7.9909 | 434  | 1.0693          | 0.7052   |
| 0.7838        | 8.9863 | 488  | 1.0308          | 0.7138   |
| 0.7813        | 9.9452 | 540  | 0.9886          | 0.7247   |


### Framework versions

- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3