---
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-clp
  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-clp

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: 0.5263
- Wer: 0.4067

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 4.858         | 5.0   | 200  | 2.6999          | 1.0    |
| 2.2652        | 10.0  | 400  | 1.2382          | 1.0042 |
| 0.8587        | 15.0  | 600  | 0.5870          | 0.6960 |
| 0.3893        | 20.0  | 800  | 0.5675          | 0.6122 |
| 0.257         | 25.0  | 1000 | 0.4928          | 0.4822 |
| 0.1862        | 30.0  | 1200 | 0.4408          | 0.4885 |
| 0.148         | 35.0  | 1400 | 0.5587          | 0.4298 |
| 0.1203        | 40.0  | 1600 | 0.5393          | 0.4549 |
| 0.1094        | 45.0  | 1800 | 0.4889          | 0.4403 |
| 0.0908        | 50.0  | 2000 | 0.6539          | 0.4298 |
| 0.0766        | 55.0  | 2200 | 0.4469          | 0.4109 |
| 0.0675        | 60.0  | 2400 | 0.4109          | 0.4004 |
| 0.0622        | 65.0  | 2600 | 0.4543          | 0.3962 |
| 0.0617        | 70.0  | 2800 | 0.5189          | 0.3920 |
| 0.0529        | 75.0  | 3000 | 0.4261          | 0.3878 |
| 0.0514        | 80.0  | 3200 | 0.5161          | 0.3920 |
| 0.0473        | 85.0  | 3400 | 0.4789          | 0.3983 |
| 0.0419        | 90.0  | 3600 | 0.5161          | 0.4088 |
| 0.0405        | 95.0  | 3800 | 0.5263          | 0.4067 |


### Framework versions

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