---
language:
- ev
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-large-xlsr-53
  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-large-xlsr-53

This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the Evenki dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8728
- Wer: 65.9678

## 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: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- 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: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer     |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 8.8625        | 0.6279  | 100  | 4.7672          | 100.0   |
| 3.5933        | 1.2559  | 200  | 3.5125          | 100.0   |
| 3.4942        | 1.8838  | 300  | 3.4852          | 100.0   |
| 3.5053        | 2.5118  | 400  | 3.4885          | 100.0   |
| 3.2185        | 3.1397  | 500  | 2.8873          | 100.0   |
| 2.2076        | 3.7677  | 600  | 1.6237          | 99.9844 |
| 1.6129        | 4.3956  | 700  | 1.2754          | 92.5833 |
| 1.5995        | 5.0235  | 800  | 1.1585          | 84.6033 |
| 1.333         | 5.6515  | 900  | 1.0689          | 80.4882 |
| 1.2571        | 6.2794  | 1000 | 1.0283          | 77.4840 |
| 1.1675        | 6.9074  | 1100 | 0.9761          | 75.3716 |
| 1.1193        | 7.5353  | 1200 | 0.9367          | 73.3532 |
| 1.0054        | 8.1633  | 1300 | 0.9723          | 72.4300 |
| 1.0211        | 8.7912  | 1400 | 0.8911          | 70.4115 |
| 0.9408        | 9.4192  | 1500 | 0.9405          | 70.6775 |
| 0.9115        | 10.0471 | 1600 | 0.8998          | 68.2835 |
| 0.8533        | 10.6750 | 1700 | 0.9073          | 68.3461 |
| 0.7981        | 11.3030 | 1800 | 0.8838          | 67.8141 |
| 0.8154        | 11.9309 | 1900 | 0.8872          | 66.7345 |
| 0.7603        | 12.5589 | 2000 | 0.8681          | 66.9379 |
| 0.7711        | 13.1868 | 2100 | 0.8723          | 66.5154 |
| 0.6974        | 13.8148 | 2200 | 0.8634          | 66.1242 |
| 0.7224        | 14.4427 | 2300 | 0.8728          | 65.9678 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1