transformers tensorboard safetensors wav2vec2 audio-classification generated_from_trainer base_model:facebook/wav2vec2-base license:apache-2.0 endpoints_compatible region:us
---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: my_awesome_model
  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. -->

# my_awesome_model

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3905
- Accuracy: 0.9158

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.7774        | 0.99  | 27   | 1.6708          | 0.4856   |
| 1.3665        | 1.98  | 54   | 1.1744          | 0.7739   |
| 0.9392        | 2.97  | 81   | 0.8476          | 0.8374   |
| 0.7654        | 4.0   | 109  | 0.6763          | 0.8570   |
| 0.5547        | 4.99  | 136  | 0.5508          | 0.8870   |
| 0.4244        | 5.98  | 163  | 0.4724          | 0.8985   |
| 0.371         | 6.97  | 190  | 0.4536          | 0.9054   |
| 0.3302        | 8.0   | 218  | 0.4224          | 0.9031   |
| 0.2883        | 8.99  | 245  | 0.3924          | 0.9146   |
| 0.2642        | 9.91  | 270  | 0.3905          | 0.9158   |


### Framework versions

- Transformers 4.37.0
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.1
