---
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
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# 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