---
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-nomi
  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-nomi

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: 0.3324
- Wer: 0.3245

## 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    |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 4.9773        | 6.0606  | 200  | 3.0522          | 1.0    |
| 2.8875        | 12.1212 | 400  | 2.3569          | 0.9959 |
| 1.5131        | 18.1818 | 600  | 0.5795          | 0.6024 |
| 0.4675        | 24.2424 | 800  | 0.4022          | 0.4523 |
| 0.2474        | 30.3030 | 1000 | 0.3396          | 0.4422 |
| 0.1573        | 36.3636 | 1200 | 0.3188          | 0.3611 |
| 0.1162        | 42.4242 | 1400 | 0.3450          | 0.3570 |
| 0.0858        | 48.4848 | 1600 | 0.3162          | 0.3469 |
| 0.0675        | 54.5455 | 1800 | 0.2832          | 0.3327 |
| 0.058         | 60.6061 | 2000 | 0.2904          | 0.3266 |
| 0.0415        | 66.6667 | 2200 | 0.3555          | 0.3306 |
| 0.0348        | 72.7273 | 2400 | 0.3116          | 0.3327 |
| 0.0234        | 78.7879 | 2600 | 0.2944          | 0.3245 |
| 0.0215        | 84.8485 | 2800 | 0.3259          | 0.3266 |
| 0.0208        | 90.9091 | 3000 | 0.3312          | 0.3185 |
| 0.0168        | 96.9697 | 3200 | 0.3324          | 0.3245 |


### Framework versions

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