---
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2_xls_r_300m_BIG-C_Bemba_50hr_v3
  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_xls_r_300m_BIG-C_Bemba_50hr_v3

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: 0.4961
- Model Preparation Time: 0.006
- Wer: 0.4359
- Cer: 0.1111

## 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: 0.0003
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 500
- num_epochs: 100
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Wer    | Cer    |
|:-------------:|:-----:|:----:|:---------------:|:----------------------:|:------:|:------:|
| 3.6745        | 1.0   | 394  | inf             | 0.006                  | 0.6294 | 0.1564 |
| 0.6444        | 2.0   | 788  | inf             | 0.006                  | 0.4910 | 0.1283 |
| 0.5606        | 3.0   | 1182 | inf             | 0.006                  | 0.4686 | 0.1203 |
| 0.521         | 4.0   | 1576 | inf             | 0.006                  | 0.4644 | 0.1227 |
| 0.4858        | 5.0   | 1970 | inf             | 0.006                  | 0.4451 | 0.1157 |
| 0.4571        | 6.0   | 2364 | inf             | 0.006                  | 0.4622 | 0.1212 |
| 0.4348        | 7.0   | 2758 | inf             | 0.006                  | 0.4716 | 0.1417 |
| 0.7234        | 8.0   | 3152 | inf             | 0.006                  | 0.9825 | 0.3581 |
| 1.7422        | 9.0   | 3546 | inf             | 0.006                  | 0.9813 | 0.3970 |
| 1.819         | 10.0  | 3940 | inf             | 0.006                  | 0.9996 | 0.5327 |
| 1.0484        | 11.0  | 4334 | inf             | 0.006                  | 0.5059 | 0.1368 |
| 1.9919        | 12.0  | 4728 | nan             | 0.006                  | 0.9999 | 0.6240 |
| 0.8944        | 13.0  | 5122 | nan             | 0.006                  | 0.9999 | 0.6240 |
| 2.7123        | 14.0  | 5516 | nan             | 0.006                  | 1.0    | 1.0    |
| 0.0           | 15.0  | 5910 | nan             | 0.006                  | 1.0    | 1.0    |
| 0.0           | 16.0  | 6304 | nan             | 0.006                  | 1.0    | 1.0    |
| 0.0           | 17.0  | 6698 | nan             | 0.006                  | 1.0    | 1.0    |
| 0.0           | 18.0  | 7092 | nan             | 0.006                  | 1.0    | 1.0    |
| 0.0           | 19.0  | 7486 | nan             | 0.006                  | 1.0    | 1.0    |
| 0.0           | 20.0  | 7880 | nan             | 0.006                  | 1.0    | 1.0    |


### Framework versions

- Transformers 4.44.0
- Pytorch 2.2.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1