---
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-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-a-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: 0.6748
- Wer: 0.3390

## 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    |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 4.3851        | 2.3529  | 200  | 2.4270          | 1.0    |
| 1.3933        | 4.7059  | 400  | 0.5187          | 0.6193 |
| 0.2417        | 7.0588  | 600  | 0.4328          | 0.4403 |
| 0.1174        | 9.4118  | 800  | 0.4113          | 0.4186 |
| 0.08          | 11.7647 | 1000 | 0.3914          | 0.3589 |
| 0.0509        | 14.1176 | 1200 | 0.4065          | 0.3665 |
| 0.0445        | 16.4706 | 1400 | 0.4714          | 0.3636 |
| 0.0329        | 18.8235 | 1600 | 0.3930          | 0.3561 |
| 0.0315        | 21.1765 | 1800 | 0.5501          | 0.3655 |
| 0.0298        | 23.5294 | 2000 | 0.4462          | 0.3561 |
| 0.0366        | 25.8824 | 2200 | 0.4993          | 0.3447 |
| 0.0259        | 28.2353 | 2400 | 0.5077          | 0.3561 |
| 0.0197        | 30.5882 | 2600 | 0.5029          | 0.3466 |
| 0.0229        | 32.9412 | 2800 | 0.4760          | 0.3400 |
| 0.0174        | 35.2941 | 3000 | 0.5118          | 0.3475 |
| 0.0102        | 37.6471 | 3200 | 0.5630          | 0.3428 |
| 0.0104        | 40.0    | 3400 | 0.5598          | 0.3400 |
| 0.015         | 42.3529 | 3600 | 0.5226          | 0.3428 |
| 0.0102        | 44.7059 | 3800 | 0.5421          | 0.3513 |
| 0.012         | 47.0588 | 4000 | 0.5936          | 0.3456 |
| 0.0101        | 49.4118 | 4200 | 0.5772          | 0.3485 |
| 0.009         | 51.7647 | 4400 | 0.5759          | 0.3438 |
| 0.0104        | 54.1176 | 4600 | 0.5755          | 0.3400 |
| 0.0118        | 56.4706 | 4800 | 0.5868          | 0.3362 |
| 0.0118        | 58.8235 | 5000 | 0.6174          | 0.3456 |
| 0.0109        | 61.1765 | 5200 | 0.6037          | 0.3390 |
| 0.0086        | 63.5294 | 5400 | 0.5903          | 0.3447 |
| 0.0039        | 65.8824 | 5600 | 0.5894          | 0.3428 |
| 0.0058        | 68.2353 | 5800 | 0.6388          | 0.3428 |
| 0.0044        | 70.5882 | 6000 | 0.6378          | 0.3390 |
| 0.0032        | 72.9412 | 6200 | 0.6868          | 0.3409 |
| 0.0057        | 75.2941 | 6400 | 0.6439          | 0.3419 |
| 0.0034        | 77.6471 | 6600 | 0.6888          | 0.3381 |
| 0.0022        | 80.0    | 6800 | 0.7217          | 0.3381 |
| 0.0032        | 82.3529 | 7000 | 0.5946          | 0.3371 |
| 0.0033        | 84.7059 | 7200 | 0.6650          | 0.3390 |
| 0.0018        | 87.0588 | 7400 | 0.6844          | 0.3371 |
| 0.0026        | 89.4118 | 7600 | 0.7199          | 0.3409 |
| 0.0028        | 91.7647 | 7800 | 0.6868          | 0.3381 |
| 0.002         | 94.1176 | 8000 | 0.6752          | 0.3409 |
| 0.0013        | 96.4706 | 8200 | 0.6788          | 0.3390 |
| 0.0011        | 98.8235 | 8400 | 0.6748          | 0.3390 |


### Framework versions

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