---
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-nomimose
  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-nomimose

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: 0.9684
- Wer: 0.4369

## 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    |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 4.9556        | 3.3932  | 200  | 3.0924          | 1.0    |
| 3.024         | 6.7863  | 400  | 2.8991          | 0.9943 |
| 2.7554        | 10.1709 | 600  | 2.4531          | 1.0    |
| 2.1877        | 13.5641 | 800  | 1.6865          | 0.9181 |
| 1.247         | 16.9573 | 1000 | 1.1531          | 0.7247 |
| 0.7161        | 20.3419 | 1200 | 1.0237          | 0.6052 |
| 0.4613        | 23.7350 | 1400 | 0.9152          | 0.5631 |
| 0.3173        | 27.1197 | 1600 | 0.8917          | 0.5165 |
| 0.2399        | 30.5128 | 1800 | 0.8512          | 0.5256 |
| 0.1871        | 33.9060 | 2000 | 0.9078          | 0.4937 |
| 0.1536        | 37.2906 | 2200 | 0.9574          | 0.4972 |
| 0.1259        | 40.6838 | 2400 | 0.9938          | 0.4903 |
| 0.1095        | 44.0684 | 2600 | 1.0196          | 0.4994 |
| 0.0947        | 47.4615 | 2800 | 0.9235          | 0.4778 |
| 0.073         | 50.8547 | 3000 | 1.1352          | 0.4972 |
| 0.068         | 54.2393 | 3200 | 0.9595          | 0.4778 |
| 0.0562        | 57.6325 | 3400 | 1.0105          | 0.4710 |
| 0.0564        | 61.0171 | 3600 | 1.0297          | 0.4744 |
| 0.052         | 64.4103 | 3800 | 1.0371          | 0.4562 |
| 0.0371        | 67.8034 | 4000 | 1.0999          | 0.4733 |
| 0.034         | 71.1880 | 4200 | 1.0486          | 0.4699 |
| 0.039         | 74.5812 | 4400 | 0.9800          | 0.4585 |
| 0.031         | 77.9744 | 4600 | 0.9614          | 0.4494 |
| 0.0323        | 81.3590 | 4800 | 0.9838          | 0.4551 |
| 0.0229        | 84.7521 | 5000 | 1.0129          | 0.4334 |
| 0.0232        | 88.1368 | 5200 | 0.9266          | 0.4243 |
| 0.0144        | 91.5299 | 5400 | 0.9751          | 0.4334 |
| 0.0178        | 94.9231 | 5600 | 0.9619          | 0.4369 |
| 0.0147        | 98.3077 | 5800 | 0.9684          | 0.4369 |


### Framework versions

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