---
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-large-xls-r-300m-lg-cv-10hr-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. -->

[<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/o0fw7ke6)
# wav2vec2-large-xls-r-300m-lg-cv-10hr-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: 0.6399
- Wer: 0.5490
- Cer: 0.1258

## 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: 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 | Wer    | Cer    |
|:-------------:|:-------:|:----:|:---------------:|:------:|:------:|
| No log        | 0.9948  | 95   | 5.7544          | 1.0    | 1.0    |
| 11.4782       | 2.0     | 191  | 3.4141          | 1.0    | 1.0    |
| 3.8877        | 2.9948  | 286  | 2.9705          | 1.0    | 1.0    |
| 3.0666        | 4.0     | 382  | 2.8116          | 1.0    | 1.0    |
| 2.8721        | 4.9948  | 477  | 0.9460          | 0.9262 | 0.2276 |
| 1.6147        | 6.0     | 573  | 0.6163          | 0.8134 | 0.1855 |
| 0.6412        | 6.9948  | 668  | 0.4726          | 0.6816 | 0.1425 |
| 0.4424        | 8.0     | 764  | 0.4475          | 0.6449 | 0.1306 |
| 0.3408        | 8.9948  | 859  | 0.4403          | 0.6429 | 0.1310 |
| 0.2786        | 10.0    | 955  | 0.4409          | 0.6139 | 0.1252 |
| 0.24          | 10.9948 | 1050 | 0.4206          | 0.5878 | 0.1218 |
| 0.2111        | 12.0    | 1146 | 0.4501          | 0.5916 | 0.1194 |
| 0.1881        | 12.9948 | 1241 | 0.4514          | 0.5645 | 0.1140 |
| 0.1672        | 14.0    | 1337 | 0.4553          | 0.5761 | 0.1224 |
| 0.1532        | 14.9948 | 1432 | 0.4780          | 0.5764 | 0.1179 |
| 0.1421        | 16.0    | 1528 | 0.4795          | 0.5767 | 0.1177 |
| 0.1357        | 16.9948 | 1623 | 0.4573          | 0.5643 | 0.1189 |
| 0.1248        | 18.0    | 1719 | 0.4774          | 0.5679 | 0.1202 |
| 0.1176        | 18.9948 | 1814 | 0.5095          | 0.5659 | 0.1186 |
| 0.111         | 20.0    | 1910 | 0.4775          | 0.5562 | 0.1138 |
| 0.1093        | 20.9948 | 2005 | 0.5052          | 0.5465 | 0.1115 |
| 0.1017        | 22.0    | 2101 | 0.5074          | 0.5464 | 0.1123 |
| 0.1017        | 22.9948 | 2196 | 0.5003          | 0.5419 | 0.1135 |
| 0.0965        | 24.0    | 2292 | 0.5247          | 0.5420 | 0.1130 |
| 0.0947        | 24.9948 | 2387 | 0.5224          | 0.5474 | 0.1152 |
| 0.0903        | 26.0    | 2483 | 0.5124          | 0.5250 | 0.1089 |
| 0.0865        | 26.9948 | 2578 | 0.5339          | 0.5387 | 0.1100 |
| 0.0837        | 28.0    | 2674 | 0.5362          | 0.5340 | 0.1128 |
| 0.0836        | 28.9948 | 2769 | 0.5354          | 0.5276 | 0.1095 |
| 0.0773        | 30.0    | 2865 | 0.5512          | 0.5352 | 0.1101 |
| 0.075         | 30.9948 | 2960 | 0.5162          | 0.5102 | 0.1058 |
| 0.0723        | 32.0    | 3056 | 0.5296          | 0.5236 | 0.1057 |
| 0.0764        | 32.9948 | 3151 | 0.5447          | 0.5289 | 0.1083 |
| 0.0706        | 34.0    | 3247 | 0.5291          | 0.5355 | 0.1138 |
| 0.0694        | 34.9948 | 3342 | 0.5314          | 0.5244 | 0.1116 |
| 0.0679        | 36.0    | 3438 | 0.5199          | 0.5215 | 0.1135 |
| 0.0645        | 36.9948 | 3533 | 0.5555          | 0.5244 | 0.1118 |
| 0.0623        | 38.0    | 3629 | 0.5392          | 0.5266 | 0.1141 |
| 0.0622        | 38.9948 | 3724 | 0.5500          | 0.5248 | 0.1125 |
| 0.06          | 40.0    | 3820 | 0.5467          | 0.5197 | 0.1121 |
| 0.0598        | 40.9948 | 3915 | 0.5405          | 0.5161 | 0.1120 |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.2.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1