---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-E50
  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. -->

# wav2vec2-E50

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 4.4959
- Cer: 89.8179

## 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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- 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: 50
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Cer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 28.4775       | 0.2581 | 200  | 5.5054          | 100.0   |
| 4.6583        | 0.5161 | 400  | 5.0085          | 91.3690 |
| 4.4404        | 0.7742 | 600  | 5.2442          | 92.5264 |
| 4.3414        | 1.0323 | 800  | 4.9330          | 90.7109 |
| 4.3064        | 1.2903 | 1000 | 4.8601          | 90.7814 |
| 4.2331        | 1.5484 | 1200 | 4.9136          | 92.1034 |
| 4.2258        | 1.8065 | 1400 | 5.0350          | 90.3702 |
| 4.1731        | 2.0645 | 1600 | 5.0754          | 90.3995 |
| 4.1586        | 2.3226 | 1800 | 4.7405          | 89.2773 |
| 4.1386        | 2.5806 | 2000 | 4.6875          | 90.8578 |
| 4.1294        | 2.8387 | 2200 | 4.4959          | 89.8179 |


### Framework versions

- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0