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---
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-130hr-v1
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/zui44xp5)
# wav2vec2-large-xls-r-300m-lg-cv-130hr-v1
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: 0.4019
- Wer: 0.2092
- Cer: 0.0456
## 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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 500
- num_epochs: 30
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|:-------------:|:-----:|:------:|:---------------:|:------:|:------:|
| 0.7325 | 1.0 | 5194 | 0.2760 | 0.3441 | 0.0731 |
| 0.2056 | 2.0 | 10388 | 0.2507 | 0.2835 | 0.0629 |
| 0.1744 | 3.0 | 15582 | 0.2414 | 0.2721 | 0.0605 |
| 0.155 | 4.0 | 20776 | 0.2359 | 0.2618 | 0.0584 |
| 0.143 | 5.0 | 25970 | 0.2354 | 0.2577 | 0.0575 |
| 0.131 | 6.0 | 31164 | 0.2400 | 0.2551 | 0.0570 |
| 0.1208 | 7.0 | 36358 | 0.2460 | 0.2482 | 0.0555 |
| 0.1102 | 8.0 | 41552 | 0.2553 | 0.2439 | 0.0548 |
| 0.1001 | 9.0 | 46746 | 0.2441 | 0.2455 | 0.0547 |
| 0.0898 | 10.0 | 51940 | 0.2463 | 0.2423 | 0.0543 |
| 0.0795 | 11.0 | 57134 | 0.2577 | 0.2400 | 0.0528 |
| 0.0701 | 12.0 | 62328 | 0.2677 | 0.2374 | 0.0522 |
| 0.0609 | 13.0 | 67522 | 0.2741 | 0.2405 | 0.0527 |
| 0.0538 | 14.0 | 72716 | 0.2933 | 0.2396 | 0.0523 |
| 0.0471 | 15.0 | 77910 | 0.3096 | 0.2352 | 0.0517 |
| 0.0416 | 16.0 | 83104 | 0.3165 | 0.2311 | 0.0503 |
| 0.0374 | 17.0 | 88298 | 0.3294 | 0.2328 | 0.0505 |
| 0.0335 | 18.0 | 93492 | 0.3414 | 0.2325 | 0.0501 |
| 0.0301 | 19.0 | 98686 | 0.3379 | 0.2255 | 0.0487 |
| 0.0276 | 20.0 | 103880 | 0.3578 | 0.2220 | 0.0482 |
| 0.0253 | 21.0 | 109074 | 0.3701 | 0.2181 | 0.0476 |
| 0.0236 | 22.0 | 114268 | 0.3769 | 0.2181 | 0.0474 |
| 0.0217 | 23.0 | 119462 | 0.3808 | 0.2155 | 0.0470 |
| 0.0204 | 24.0 | 124656 | 0.3917 | 0.2124 | 0.0464 |
| 0.0193 | 25.0 | 129850 | 0.3963 | 0.2110 | 0.0459 |
| 0.0184 | 26.0 | 135044 | 0.3956 | 0.2111 | 0.0458 |
| 0.0174 | 27.0 | 140238 | 0.4046 | 0.2109 | 0.0459 |
| 0.0174 | 28.0 | 145432 | 0.3997 | 0.2096 | 0.0457 |
| 0.0169 | 29.0 | 150626 | 0.4014 | 0.2093 | 0.0456 |
| 0.0171 | 30.0 | 155820 | 0.4019 | 0.2092 | 0.0456 |
### Framework versions
- Transformers 4.42.3
- Pytorch 2.2.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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