---
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- wer
model-index:
- name: tachiwin_totonac
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: audiofolder
      type: audiofolder
      config: ljcamargo--totonac_alpha_1
      split: test
      args: ljcamargo--totonac_alpha_1
    metrics:
    - name: Wer
      type: wer
      value: 0.6465189873417722
---

<!-- 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. -->

# tachiwin_totonac

This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the audiofolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7535
- Wer: 0.6465

## 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: 0.0003
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 90

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 5.1063        | 5.19  | 200  | 2.9834          | 1.0    |
| 2.9016        | 10.39 | 400  | 2.4405          | 0.9959 |
| 1.7606        | 15.58 | 600  | 1.1942          | 0.8532 |
| 1.0549        | 20.78 | 800  | 1.1132          | 0.7788 |
| 0.7553        | 25.97 | 1000 | 1.1224          | 0.6899 |
| 0.6639        | 31.51 | 1200 | 1.2641          | 0.7082 |
| 0.5344        | 36.7  | 1400 | 1.3247          | 0.6835 |
| 0.4527        | 41.9  | 1600 | 1.3915          | 0.7022 |
| 0.3839        | 47.09 | 1800 | 1.4051          | 0.6791 |
| 0.3065        | 52.29 | 2000 | 1.3899          | 0.6706 |
| 0.2714        | 57.48 | 2200 | 1.5455          | 0.6573 |
| 0.2437        | 62.68 | 2400 | 1.6798          | 0.6601 |
| 0.2103        | 67.87 | 2600 | 1.7406          | 0.6674 |
| 0.1899        | 73.06 | 2800 | 1.7625          | 0.6522 |
| 0.1841        | 78.26 | 3000 | 1.7443          | 0.6535 |
| 0.1544        | 83.45 | 3200 | 1.7405          | 0.6465 |
| 0.1461        | 88.65 | 3400 | 1.7535          | 0.6465 |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3