---
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-nomo
  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-nomo

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: 1.0423
- Wer: 0.3916

## 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    |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 4.7334        | 6.4590  | 200  | 3.1082          | 1.0    |
| 2.9544        | 12.9180 | 400  | 2.8429          | 0.9956 |
| 2.0771        | 19.3607 | 600  | 1.2204          | 0.8341 |
| 0.7271        | 25.8197 | 800  | 1.0868          | 0.5531 |
| 0.3103        | 32.2623 | 1000 | 1.0536          | 0.4912 |
| 0.1852        | 38.7213 | 1200 | 0.9030          | 0.4469 |
| 0.1399        | 45.1639 | 1400 | 0.8980          | 0.4491 |
| 0.0864        | 51.6230 | 1600 | 0.8315          | 0.4292 |
| 0.0643        | 58.0656 | 1800 | 0.9488          | 0.4004 |
| 0.0525        | 64.5246 | 2000 | 0.9354          | 0.4137 |
| 0.0455        | 70.9836 | 2200 | 0.9717          | 0.4093 |
| 0.0383        | 77.4262 | 2400 | 0.9781          | 0.4004 |
| 0.0261        | 83.8852 | 2600 | 1.1244          | 0.3938 |
| 0.0265        | 90.3279 | 2800 | 1.0439          | 0.4004 |
| 0.0197        | 96.7869 | 3000 | 1.0423          | 0.3916 |


### Framework versions

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