---
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: nyankole_wav2vec2-runpod-unf-large
  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/mbalireshawal-makerere-university/huggingface/runs/1l4ekc0h)
[<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/mbalireshawal-makerere-university/huggingface/runs/1l4ekc0h)
[<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/mbalireshawal-makerere-university/huggingface/runs/1l4ekc0h)
[<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/mbalireshawal-makerere-university/huggingface/runs/1l4ekc0h)
[<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/mbalireshawal-makerere-university/huggingface/runs/1l4ekc0h)
# nyankole_wav2vec2-runpod-unf-large

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: 830.9091
- Wer: 0.6101

## 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: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 7399.694      | 1.0   | 53   | 3616.8877       | 1.0    |
| 7452.8927     | 2.0   | 106  | 3606.0696       | 1.0    |
| 7321.2547     | 3.0   | 159  | 3614.7188       | 1.0    |
| 7283.513      | 4.0   | 212  | 3665.7957       | 1.0    |
| 7260.0973     | 5.0   | 265  | 3556.3738       | 1.0    |
| 7184.4652     | 6.0   | 318  | 3440.7732       | 1.0    |
| 6526.0413     | 7.0   | 371  | 2693.0374       | 1.0    |
| 5025.6185     | 8.0   | 424  | 1748.6117       | 0.9985 |
| 3761.0044     | 9.0   | 477  | 1390.0330       | 0.8946 |
| 3265.3567     | 10.0  | 530  | 1185.7458       | 0.8108 |
| 2818.3317     | 11.0  | 583  | 1076.5151       | 0.7582 |
| 2666.5274     | 12.0  | 636  | 1016.1800       | 0.7206 |
| 2484.5062     | 13.0  | 689  | 1017.9598       | 0.7026 |
| 2363.0265     | 14.0  | 742  | 935.6443        | 0.6879 |
| 2215.8507     | 15.0  | 795  | 926.4963        | 0.6670 |
| 2169.1753     | 16.0  | 848  | 892.7558        | 0.6608 |
| 2054.9318     | 17.0  | 901  | 885.1797        | 0.6461 |
| 2001.906      | 18.0  | 954  | 869.5634        | 0.6369 |
| 2011.2323     | 19.0  | 1007 | 857.0482        | 0.6317 |
| 1900.8241     | 20.0  | 1060 | 855.6694        | 0.625  |
| 1869.7319     | 21.0  | 1113 | 842.1160        | 0.6296 |
| 1809.5601     | 22.0  | 1166 | 838.9195        | 0.6219 |
| 1828.7354     | 23.0  | 1219 | 830.1293        | 0.6198 |
| 1804.8732     | 24.0  | 1272 | 835.9683        | 0.6173 |
| 1775.2409     | 25.0  | 1325 | 831.1539        | 0.6103 |
| 1805.726      | 26.0  | 1378 | 831.0961        | 0.6157 |
| 1738.365      | 27.0  | 1431 | 831.4120        | 0.6126 |
| 1802.3348     | 28.0  | 1484 | 831.5934        | 0.6113 |
| 1806.6047     | 29.0  | 1537 | 831.4467        | 0.6101 |
| 1788.635      | 30.0  | 1590 | 830.9091        | 0.6101 |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1