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---
library_name: transformers
license: mit
base_model: facebook/w2v-bert-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: w2v-bert-2.0-CV_Fleurs-lg-50hrs-v4
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-CV_Fleurs-lg-50hrs-v4
This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3482
- Wer: 0.2832
- Cer: 0.0557
## 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: 3e-05
- train_batch_size: 8
- eval_batch_size: 4
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 100
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|
| 1.9126 | 1.0 | 3160 | 0.3415 | 0.4010 | 0.0853 |
| 0.2463 | 2.0 | 6320 | 0.2633 | 0.3447 | 0.0670 |
| 0.1946 | 3.0 | 9480 | 0.2369 | 0.3201 | 0.0633 |
| 0.168 | 4.0 | 12640 | 0.2246 | 0.3098 | 0.0607 |
| 0.15 | 5.0 | 15800 | 0.2179 | 0.3205 | 0.0595 |
| 0.1394 | 6.0 | 18960 | 0.2245 | 0.3060 | 0.0594 |
| 0.1283 | 7.0 | 22120 | 0.2173 | 0.3029 | 0.0600 |
| 0.1219 | 8.0 | 25280 | 0.2203 | 0.3183 | 0.0583 |
| 0.1155 | 9.0 | 28440 | 0.2148 | 0.2923 | 0.0573 |
| 0.1117 | 10.0 | 31600 | 0.2334 | 0.3037 | 0.0586 |
| 0.1031 | 11.0 | 34760 | 0.2162 | 0.2876 | 0.0578 |
| 0.0908 | 12.0 | 37920 | 0.2210 | 0.2883 | 0.0560 |
| 0.0804 | 13.0 | 41080 | 0.2271 | 0.3001 | 0.0581 |
| 0.0706 | 14.0 | 44240 | 0.2403 | 0.2753 | 0.0540 |
| 0.0602 | 15.0 | 47400 | 0.2528 | 0.2955 | 0.0578 |
| 0.0512 | 16.0 | 50560 | 0.2695 | 0.2883 | 0.0555 |
| 0.0432 | 17.0 | 53720 | 0.2597 | 0.2903 | 0.0554 |
| 0.0367 | 18.0 | 56880 | 0.2764 | 0.2850 | 0.0556 |
| 0.0317 | 19.0 | 60040 | 0.2954 | 0.2908 | 0.0570 |
| 0.0267 | 20.0 | 63200 | 0.3053 | 0.2878 | 0.0556 |
| 0.0236 | 21.0 | 66360 | 0.3087 | 0.2868 | 0.0565 |
| 0.0208 | 22.0 | 69520 | 0.2907 | 0.2970 | 0.0584 |
| 0.0175 | 23.0 | 72680 | 0.3274 | 0.2838 | 0.0550 |
| 0.0169 | 24.0 | 75840 | 0.3482 | 0.2832 | 0.0557 |
### Framework versions
- Transformers 4.46.0
- Pytorch 2.1.0+cu118
- Datasets 3.0.2
- Tokenizers 0.20.1
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