---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: xlsr-a-nomi-ag
  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-a-nomi-ag

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: 0.3211
- Wer: 0.3369

## 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: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer    |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 4.5146        | 2.2727  | 200  | 2.5284          | 1.0    |
| 1.4558        | 4.5455  | 400  | 0.4417          | 0.6139 |
| 0.253         | 6.8182  | 600  | 0.2623          | 0.4254 |
| 0.1064        | 9.0909  | 800  | 0.3151          | 0.4013 |
| 0.0715        | 11.3636 | 1000 | 0.2867          | 0.3744 |
| 0.0575        | 13.6364 | 1200 | 0.3176          | 0.3584 |
| 0.0445        | 15.9091 | 1400 | 0.3323          | 0.3432 |
| 0.029         | 18.1818 | 1600 | 0.3549          | 0.3467 |
| 0.0291        | 20.4545 | 1800 | 0.2824          | 0.3458 |
| 0.0196        | 22.7273 | 2000 | 0.3145          | 0.3414 |
| 0.0205        | 25.0    | 2200 | 0.3013          | 0.3396 |
| 0.0168        | 27.2727 | 2400 | 0.3207          | 0.3387 |
| 0.0136        | 29.5455 | 2600 | 0.3306          | 0.3333 |
| 0.0109        | 31.8182 | 2800 | 0.3197          | 0.3324 |
| 0.0077        | 34.0909 | 3000 | 0.3511          | 0.3378 |
| 0.0082        | 36.3636 | 3200 | 0.3408          | 0.3342 |
| 0.0088        | 38.6364 | 3400 | 0.3354          | 0.3369 |
| 0.0066        | 40.9091 | 3600 | 0.3246          | 0.3360 |
| 0.0035        | 43.1818 | 3800 | 0.3295          | 0.3369 |
| 0.0044        | 45.4545 | 4000 | 0.3220          | 0.3369 |
| 0.0049        | 47.7273 | 4200 | 0.3196          | 0.3378 |
| 0.0029        | 50.0    | 4400 | 0.3211          | 0.3369 |


### Framework versions

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