---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec-sq-3.0
  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. -->

# wav2vec-sq-3.0

This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9327
- Wer: 0.6953

## 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: 1e-05
- train_batch_size: 32
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- 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: 250
- training_steps: 2500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 6.166         | 0.2657 | 250  | 2.9837          | 1.0    |
| 5.9696        | 0.5313 | 500  | 2.8618          | 1.0    |
| 5.1332        | 0.7970 | 750  | 2.0889          | 0.9683 |
| 3.6118        | 1.0627 | 1000 | 1.4413          | 0.8753 |
| 2.6843        | 1.3284 | 1250 | 1.1732          | 0.8004 |
| 2.3974        | 1.5940 | 1500 | 1.0998          | 0.7510 |
| 2.2139        | 1.8597 | 1750 | 1.0167          | 0.7115 |
| 2.0901        | 2.1254 | 2000 | 0.9646          | 0.7069 |
| 2.0002        | 2.3911 | 2250 | 0.9416          | 0.6906 |
| 1.9739        | 2.6567 | 2500 | 0.9327          | 0.6953 |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0