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---
license: mit
base_model: facebook/w2v-bert-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: w2v-bert-2.0-ln-afrivoice-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. -->
# w2v-bert-2.0-ln-afrivoice-10hr-v3
This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5394
- Model Preparation Time: 0.0157
- Wer: 0.2805
- Cer: 0.0704
## 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: 5e-05
- 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
- lr_scheduler_warmup_ratio: 0.033
- num_epochs: 100
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Wer | Cer |
|:-------------:|:-------:|:----:|:---------------:|:----------------------:|:------:|:------:|
| 4.8449 | 0.9919 | 61 | 2.7369 | 0.0157 | 0.9995 | 0.9870 |
| 1.9412 | 2.0 | 123 | 0.9095 | 0.0157 | 0.4841 | 0.1700 |
| 0.7831 | 2.9919 | 184 | 0.8914 | 0.0157 | 0.4018 | 0.1424 |
| 0.67 | 4.0 | 246 | 0.7633 | 0.0157 | 0.3919 | 0.1391 |
| 0.5982 | 4.9919 | 307 | 0.8712 | 0.0157 | 0.3514 | 0.1349 |
| 0.5577 | 6.0 | 369 | 0.6596 | 0.0157 | 0.4425 | 0.1566 |
| 0.4945 | 6.9919 | 430 | 0.7157 | 0.0157 | 0.3838 | 0.1419 |
| 0.4363 | 8.0 | 492 | 0.7981 | 0.0157 | 0.3582 | 0.1324 |
| 0.395 | 8.9919 | 553 | 0.7956 | 0.0157 | 0.3483 | 0.1310 |
| 0.3416 | 10.0 | 615 | 0.7110 | 0.0157 | 0.4082 | 0.1571 |
| 0.3181 | 10.9919 | 676 | 0.8728 | 0.0157 | 0.3680 | 0.1334 |
| 0.2837 | 12.0 | 738 | 0.8389 | 0.0157 | 0.3656 | 0.1361 |
| 0.2482 | 12.9919 | 799 | 0.9984 | 0.0157 | 0.3582 | 0.1296 |
| 0.224 | 14.0 | 861 | 0.8696 | 0.0157 | 0.3971 | 0.1515 |
| 0.204 | 14.9919 | 922 | 1.0671 | 0.0157 | 0.3563 | 0.1312 |
| 0.1665 | 16.0 | 984 | 1.0956 | 0.0157 | 0.3622 | 0.1329 |
| 0.1507 | 16.9919 | 1045 | 1.4699 | 0.0157 | 0.3481 | 0.1297 |
| 0.1144 | 18.0 | 1107 | 1.4821 | 0.0157 | 0.3566 | 0.1299 |
| 0.1327 | 18.9919 | 1168 | 1.2253 | 0.0157 | 0.3699 | 0.1352 |
| 0.1085 | 20.0 | 1230 | 1.2042 | 0.0157 | 0.3929 | 0.1452 |
| 0.0694 | 20.9919 | 1291 | 1.4515 | 0.0157 | 0.3681 | 0.1317 |
| 0.0476 | 22.0 | 1353 | 1.5795 | 0.0157 | 0.3551 | 0.1301 |
| 0.0357 | 22.9919 | 1414 | 1.5949 | 0.0157 | 0.3527 | 0.1300 |
| 0.0241 | 24.0 | 1476 | 1.7094 | 0.0157 | 0.3555 | 0.1304 |
| 0.017 | 24.9919 | 1537 | 1.7941 | 0.0157 | 0.3577 | 0.1311 |
| 0.0128 | 26.0 | 1599 | 1.8157 | 0.0157 | 0.3555 | 0.1300 |
| 0.0132 | 26.9919 | 1660 | 1.8541 | 0.0157 | 0.3621 | 0.1324 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.1.0+cu118
- Datasets 2.20.0
- Tokenizers 0.19.1
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