pytorch tensorboard wav2vec2 transformers generated_from_trainer license:apache-2.0 model-index
---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: wav2vec2-large-xls-r-300m-dementianet
  results: []
---

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# wav2vec2-large-xls-r-300m-dementianet

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3430
- Accuracy: 0.4062

## 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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 22
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.3845        | 3.33  | 40   | 1.3556          | 0.3125   |
| 1.3659        | 6.67  | 80   | 1.3602          | 0.3125   |
| 1.3619        | 10.0  | 120  | 1.3569          | 0.3125   |
| 1.3575        | 13.33 | 160  | 1.3509          | 0.3125   |
| 1.3356        | 16.67 | 200  | 1.3599          | 0.3125   |
| 1.3166        | 20.0  | 240  | 1.3430          | 0.4062   |


### Framework versions

- Transformers 4.14.1
- Pytorch 1.10.0+cu111
- Datasets 1.16.1
- Tokenizers 0.10.3
