---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: wav2vec2transformerEMR3
  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. -->

# wav2vec2transformerEMR3

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: 0.6589
- Accuracy: 0.7916
- Precision: 0.7918
- Recall: 0.7916
- F1: 0.7896

## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- 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_steps: 500
- num_epochs: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.4706        | 1.6420  | 500  | 1.4207          | 0.5409   | 0.5559    | 0.5409 | 0.5180 |
| 0.953         | 3.2841  | 1000 | 0.9292          | 0.7275   | 0.7438    | 0.7275 | 0.7233 |
| 0.7575        | 4.9261  | 1500 | 0.7618          | 0.7616   | 0.7686    | 0.7616 | 0.7610 |
| 0.6084        | 6.5681  | 2000 | 0.7485          | 0.7559   | 0.7658    | 0.7559 | 0.7524 |
| 0.5221        | 8.2102  | 2500 | 0.6990          | 0.7711   | 0.7767    | 0.7711 | 0.7691 |
| 0.431         | 9.8522  | 3000 | 0.6967          | 0.7752   | 0.7796    | 0.7752 | 0.7719 |
| 0.3814        | 11.4943 | 3500 | 0.6523          | 0.7867   | 0.7875    | 0.7867 | 0.7856 |
| 0.3461        | 13.1363 | 4000 | 0.6589          | 0.7916   | 0.7918    | 0.7916 | 0.7896 |
| 0.3405        | 14.7783 | 4500 | 0.6703          | 0.7867   | 0.7878    | 0.7867 | 0.7847 |


### Framework versions

- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Tokenizers 0.20.3