---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-xls-r-ewe-50-hours
  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. -->

[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/asr-africa-research-team/ASR%20Africa/runs/dzsfyaur)
# wav2vec2-xls-r-ewe-50-hours

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: 0.8057
- Wer: 0.3383
- Cer: 0.0967

## 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: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Use OptimizerNames.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_ratio: 0.1
- num_epochs: 50

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer    | Cer    |
|:-------------:|:-------:|:----:|:---------------:|:------:|:------:|
| 11.6182       | 3.3670  | 500  | 2.5123          | 1.0    | 0.6328 |
| 1.3765        | 6.7340  | 1000 | 0.3954          | 0.3612 | 0.1030 |
| 0.8498        | 10.1010 | 1500 | 0.3698          | 0.3378 | 0.0963 |
| 0.7262        | 13.4680 | 2000 | 0.3916          | 0.3283 | 0.0956 |
| 0.6137        | 16.8350 | 2500 | 0.3981          | 0.3335 | 0.0971 |
| 0.52          | 20.2020 | 3000 | 0.4405          | 0.3467 | 0.0999 |
| 0.4375        | 23.5690 | 3500 | 0.4442          | 0.3506 | 0.1038 |
| 0.3707        | 26.9360 | 4000 | 0.5235          | 0.3471 | 0.0997 |
| 0.2992        | 30.3030 | 4500 | 0.5823          | 0.3550 | 0.1009 |
| 0.2632        | 33.6700 | 5000 | 0.6557          | 0.3449 | 0.0984 |
| 0.2181        | 37.0370 | 5500 | 0.6931          | 0.3412 | 0.0971 |
| 0.1888        | 40.4040 | 6000 | 0.7232          | 0.3420 | 0.0980 |
| 0.1653        | 43.7710 | 6500 | 0.7812          | 0.3394 | 0.0963 |
| 0.1463        | 47.1380 | 7000 | 0.8057          | 0.3383 | 0.0967 |


### Framework versions

- Transformers 4.46.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.20.3