---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: wav2vec2transformerEMR
  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. -->

# wav2vec2transformerEMR

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: 0.6501
- Accuracy: 0.7937
- Precision: 0.7945
- Recall: 0.7937
- F1: 0.7924

## 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
- 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
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.6305        | 0.8210 | 500  | 1.5561          | 0.4443   | 0.4495    | 0.4443 | 0.3962 |
| 1.1604        | 1.6420 | 1000 | 1.1252          | 0.6510   | 0.6854    | 0.6510 | 0.6491 |
| 0.9048        | 2.4631 | 1500 | 0.9422          | 0.7008   | 0.7202    | 0.7008 | 0.6987 |
| 0.7442        | 3.2841 | 2000 | 0.8200          | 0.7398   | 0.7561    | 0.7398 | 0.7358 |
| 0.6853        | 4.1051 | 2500 | 0.7475          | 0.7587   | 0.7646    | 0.7587 | 0.7555 |
| 0.6067        | 4.9261 | 3000 | 0.7000          | 0.7731   | 0.7860    | 0.7731 | 0.7748 |
| 0.5184        | 5.7471 | 3500 | 0.6890          | 0.7801   | 0.7853    | 0.7801 | 0.7778 |
| 0.4781        | 6.5681 | 4000 | 0.6983          | 0.7768   | 0.7888    | 0.7768 | 0.7752 |
| 0.4078        | 7.3892 | 4500 | 0.6654          | 0.7916   | 0.7979    | 0.7916 | 0.7913 |
| 0.4012        | 8.2102 | 5000 | 0.6759          | 0.7908   | 0.8003    | 0.7908 | 0.7897 |
| 0.3964        | 9.0312 | 5500 | 0.6501          | 0.7937   | 0.7945    | 0.7937 | 0.7924 |
| 0.315         | 9.8522 | 6000 | 0.6744          | 0.7887   | 0.7932    | 0.7887 | 0.7866 |


### Framework versions

- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Tokenizers 0.20.3