---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: xlsr-nm-nomimo
  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. -->

# xlsr-nm-nomimo

This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5614
- Wer: 0.3823

## 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: 0.0004
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- 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_steps: 132
- num_epochs: 100
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer    |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 4.9221        | 4.3478  | 200  | 3.0837          | 1.0    |
| 3.0104        | 8.6957  | 400  | 2.8149          | 1.0    |
| 2.6446        | 13.0435 | 600  | 2.2163          | 1.0    |
| 1.605         | 17.3913 | 800  | 0.9394          | 0.7108 |
| 0.6986        | 21.7391 | 1000 | 0.7128          | 0.5799 |
| 0.3653        | 26.0870 | 1200 | 0.5925          | 0.4724 |
| 0.2403        | 30.4348 | 1400 | 0.6623          | 0.4884 |
| 0.1829        | 34.7826 | 1600 | 0.6467          | 0.4564 |
| 0.1415        | 39.1304 | 1800 | 0.6584          | 0.4462 |
| 0.1127        | 43.4783 | 2000 | 0.6751          | 0.4462 |
| 0.0977        | 47.8261 | 2200 | 0.6630          | 0.4142 |
| 0.0794        | 52.1739 | 2400 | 0.5528          | 0.4230 |
| 0.0733        | 56.5217 | 2600 | 0.5641          | 0.4041 |
| 0.0574        | 60.8696 | 2800 | 0.6927          | 0.4012 |
| 0.0518        | 65.2174 | 3000 | 0.6562          | 0.3983 |
| 0.0375        | 69.5652 | 3200 | 0.6104          | 0.3852 |
| 0.0352        | 73.9130 | 3400 | 0.5976          | 0.3852 |
| 0.0297        | 78.2609 | 3600 | 0.6563          | 0.3852 |
| 0.0268        | 82.6087 | 3800 | 0.5655          | 0.3706 |
| 0.0225        | 86.9565 | 4000 | 0.6450          | 0.3823 |
| 0.0213        | 91.3043 | 4200 | 0.6029          | 0.3837 |
| 0.017         | 95.6522 | 4400 | 0.5496          | 0.3808 |
| 0.0166        | 100.0   | 4600 | 0.5614          | 0.3823 |


### Framework versions

- Transformers 4.47.0.dev0
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0