---
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-v5
  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-v5

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: 0.3755
- Wer: 0.3108
- Cer: 0.0651

## 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: 4
- eval_batch_size: 2
- 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: 80
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Wer    | Cer    |
|:-------------:|:-----:|:------:|:---------------:|:------:|:------:|
| 0.8769        | 1.0   | 6320   | 0.3126          | 0.3631 | 0.0763 |
| 0.2352        | 2.0   | 12640  | 0.2544          | 0.3542 | 0.0705 |
| 0.2161        | 3.0   | 18960  | 0.2639          | 0.3415 | 0.0695 |
| 0.2088        | 4.0   | 25280  | 0.2666          | 0.3524 | 0.0745 |
| 0.2063        | 5.0   | 31600  | 0.2863          | 0.3655 | 0.0789 |
| 0.2043        | 6.0   | 37920  | 0.2792          | 0.3409 | 0.0700 |
| 0.2036        | 7.0   | 44240  | 0.2787          | 0.3519 | 0.0736 |
| 0.2051        | 8.0   | 50560  | 0.2774          | 0.3550 | 0.0746 |
| 0.1967        | 9.0   | 56880  | 0.2710          | 0.3457 | 0.0728 |
| 0.1754        | 10.0  | 63200  | 0.2714          | 0.3425 | 0.0721 |
| 0.157         | 11.0  | 69520  | 0.2800          | 0.3490 | 0.0727 |
| 0.1411        | 12.0  | 75840  | 0.2571          | 0.3165 | 0.0671 |
| 0.1305        | 13.0  | 82160  | 0.2768          | 0.3486 | 0.0726 |
| 0.1164        | 14.0  | 88480  | 0.2963          | 0.3330 | 0.0718 |
| 0.1067        | 15.0  | 94800  | 0.2663          | 0.3131 | 0.0670 |
| 0.0954        | 16.0  | 101120 | 0.2660          | 0.3254 | 0.0667 |
| 0.0849        | 17.0  | 107440 | 0.2751          | 0.3103 | 0.0659 |
| 0.0769        | 18.0  | 113760 | 0.2721          | 0.3290 | 0.0695 |
| 0.0675        | 19.0  | 120080 | 0.2986          | 0.3148 | 0.0670 |
| 0.0606        | 20.0  | 126400 | 0.2850          | 0.3122 | 0.0653 |
| 0.0536        | 21.0  | 132720 | 0.2987          | 0.3260 | 0.0687 |
| 0.0478        | 22.0  | 139040 | 0.3226          | 0.3191 | 0.0654 |
| 0.0429        | 23.0  | 145360 | 0.2981          | 0.3373 | 0.0678 |
| 0.038         | 24.0  | 151680 | 0.3210          | 0.3172 | 0.0656 |
| 0.0343        | 25.0  | 158000 | 0.3454          | 0.3056 | 0.0635 |
| 0.0311        | 26.0  | 164320 | 0.3092          | 0.3153 | 0.0655 |
| 0.0283        | 27.0  | 170640 | 0.3285          | 0.3165 | 0.0647 |
| 0.0265        | 28.0  | 176960 | 0.3413          | 0.3125 | 0.0650 |
| 0.024         | 29.0  | 183280 | 0.3894          | 0.3062 | 0.0636 |
| 0.0223        | 30.0  | 189600 | 0.3681          | 0.3084 | 0.0645 |
| 0.0205        | 31.0  | 195920 | 0.3552          | 0.3134 | 0.0655 |
| 0.0188        | 32.0  | 202240 | 0.3656          | 0.3105 | 0.0661 |
| 0.018         | 33.0  | 208560 | 0.3640          | 0.3148 | 0.0659 |
| 0.0163        | 34.0  | 214880 | 0.3805          | 0.3099 | 0.0649 |
| 0.0153        | 35.0  | 221200 | 0.3755          | 0.3108 | 0.0651 |


### Framework versions

- Transformers 4.46.1
- Pytorch 2.1.0+cu118
- Datasets 3.1.0
- Tokenizers 0.20.1