---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- accuracy
model-index:
- name: wav2vec2-base-finetuned-mednames1
  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-base-finetuned-mednames1

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the audiofolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5263
- Accuracy: 0.9727

## 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: 5
- eval_batch_size: 5
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 20
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.2881        | 1.0   | 22   | 2.2690          | 0.2273   |
| 2.2234        | 2.0   | 44   | 2.1631          | 0.2273   |
| 1.9756        | 3.0   | 66   | 1.9277          | 0.5182   |
| 1.7191        | 4.0   | 88   | 1.6293          | 0.6818   |
| 1.4663        | 5.0   | 110  | 1.3919          | 0.7545   |
| 1.27          | 6.0   | 132  | 1.1689          | 0.8182   |
| 1.1112        | 7.0   | 154  | 1.0144          | 0.8364   |
| 0.9623        | 8.0   | 176  | 0.9137          | 0.8545   |
| 0.8764        | 9.0   | 198  | 0.7901          | 0.8909   |
| 0.7776        | 10.0  | 220  | 0.7229          | 0.8727   |
| 0.7266        | 11.0  | 242  | 0.6335          | 0.9      |
| 0.6379        | 12.0  | 264  | 0.5848          | 0.9636   |
| 0.6121        | 13.0  | 286  | 0.5509          | 0.9273   |
| 0.5732        | 14.0  | 308  | 0.5263          | 0.9727   |
| 0.5579        | 15.0  | 330  | 0.5221          | 0.9727   |


### Framework versions

- Transformers 4.27.2
- Pytorch 1.11.0+cu102
- Datasets 2.10.1
- Tokenizers 0.13.2