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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-v2
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/kxx501jb)
# wav2vec2-large-xls-r-300m-lg-cv-130hr-v2
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: 0.4316
- Wer: 0.2045
- Cer: 0.0457
## 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: 50
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|:-------------:|:-----:|:------:|:---------------:|:------:|:------:|
| 0.7427 | 1.0 | 5194 | 0.2769 | 0.3444 | 0.0749 |
| 0.2071 | 2.0 | 10388 | 0.2579 | 0.2897 | 0.0640 |
| 0.1752 | 3.0 | 15582 | 0.2357 | 0.2781 | 0.0608 |
| 0.1555 | 4.0 | 20776 | 0.2445 | 0.2626 | 0.0581 |
| 0.1437 | 5.0 | 25970 | 0.2393 | 0.2610 | 0.0584 |
| 0.1341 | 6.0 | 31164 | 0.2422 | 0.2572 | 0.0578 |
| 0.1244 | 7.0 | 36358 | 0.2358 | 0.2523 | 0.0562 |
| 0.1148 | 8.0 | 41552 | 0.2342 | 0.2532 | 0.0556 |
| 0.1077 | 9.0 | 46746 | 0.2475 | 0.2462 | 0.0551 |
| 0.0983 | 10.0 | 51940 | 0.2505 | 0.2439 | 0.0549 |
| 0.0895 | 11.0 | 57134 | 0.2556 | 0.2482 | 0.0556 |
| 0.0812 | 12.0 | 62328 | 0.2633 | 0.2492 | 0.0551 |
| 0.0727 | 13.0 | 67522 | 0.2726 | 0.2448 | 0.0546 |
| 0.0676 | 14.0 | 72716 | 0.2694 | 0.2464 | 0.0539 |
| 0.0611 | 15.0 | 77910 | 0.2984 | 0.2423 | 0.0533 |
| 0.0557 | 16.0 | 83104 | 0.2989 | 0.2418 | 0.0534 |
| 0.052 | 17.0 | 88298 | 0.3213 | 0.2402 | 0.0534 |
| 0.0478 | 18.0 | 93492 | 0.3279 | 0.2390 | 0.0532 |
| 0.0451 | 19.0 | 98686 | 0.3247 | 0.2352 | 0.0522 |
| 0.0422 | 20.0 | 103880 | 0.3452 | 0.2344 | 0.0521 |
| 0.0393 | 21.0 | 109074 | 0.3420 | 0.2384 | 0.0529 |
| 0.0378 | 22.0 | 114268 | 0.3429 | 0.2301 | 0.0509 |
| 0.036 | 23.0 | 119462 | 0.3442 | 0.2356 | 0.0520 |
| 0.0337 | 24.0 | 124656 | 0.3563 | 0.2276 | 0.0502 |
| 0.0319 | 25.0 | 129850 | 0.3480 | 0.2262 | 0.0499 |
| 0.0299 | 26.0 | 135044 | 0.3634 | 0.2233 | 0.0491 |
| 0.0281 | 27.0 | 140238 | 0.3593 | 0.2265 | 0.0499 |
| 0.0269 | 28.0 | 145432 | 0.3640 | 0.2242 | 0.0491 |
| 0.0249 | 29.0 | 150626 | 0.3713 | 0.2225 | 0.0491 |
| 0.0246 | 30.0 | 155820 | 0.3849 | 0.2193 | 0.0489 |
| 0.0228 | 31.0 | 161014 | 0.3869 | 0.2199 | 0.0482 |
| 0.0215 | 32.0 | 166208 | 0.3933 | 0.2182 | 0.0483 |
| 0.0205 | 33.0 | 171402 | 0.3920 | 0.2158 | 0.0471 |
| 0.0191 | 34.0 | 176596 | 0.3992 | 0.2166 | 0.0479 |
| 0.0183 | 35.0 | 181790 | 0.3969 | 0.2127 | 0.0467 |
| 0.0176 | 36.0 | 186984 | 0.3998 | 0.2138 | 0.0472 |
| 0.0168 | 37.0 | 192178 | 0.4068 | 0.2107 | 0.0464 |
| 0.016 | 38.0 | 197372 | 0.4216 | 0.2113 | 0.0477 |
| 0.0154 | 39.0 | 202566 | 0.4102 | 0.2102 | 0.0469 |
| 0.0149 | 40.0 | 207760 | 0.4267 | 0.2087 | 0.0465 |
| 0.0142 | 41.0 | 212954 | 0.4248 | 0.2097 | 0.0469 |
| 0.0136 | 42.0 | 218148 | 0.4254 | 0.2074 | 0.0467 |
| 0.0133 | 43.0 | 223342 | 0.4304 | 0.2074 | 0.0465 |
| 0.0131 | 44.0 | 228536 | 0.4314 | 0.2063 | 0.0462 |
| 0.0126 | 45.0 | 233730 | 0.4267 | 0.2047 | 0.0458 |
| 0.0122 | 46.0 | 238924 | 0.4291 | 0.2049 | 0.0457 |
| 0.012 | 47.0 | 244118 | 0.4305 | 0.2048 | 0.0458 |
| 0.0122 | 48.0 | 249312 | 0.4321 | 0.2046 | 0.0457 |
| 0.0121 | 49.0 | 254506 | 0.4316 | 0.2045 | 0.0457 |
| 0.0122 | 50.0 | 259700 | 0.4318 | 0.2045 | 0.0457 |
### Framework versions
- Transformers 4.42.3
- Pytorch 2.2.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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