---
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_AMMI_ALFFA-sw-10hrs-v1
  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_AMMI_ALFFA-sw-10hrs-v1

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: 0.6790
- Wer: 0.2525
- Cer: 0.0897

## 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: 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    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|
| 2.9209        | 1.0   | 710   | 0.9107          | 0.4690 | 0.1399 |
| 0.6799        | 2.0   | 1420  | 0.6451          | 0.3166 | 0.1020 |
| 0.5118        | 3.0   | 2130  | 0.6325          | 0.2602 | 0.0900 |
| 0.4435        | 4.0   | 2840  | 0.5829          | 0.2610 | 0.0951 |
| 0.3857        | 5.0   | 3550  | 0.5528          | 0.2585 | 0.0952 |
| 0.3363        | 6.0   | 4260  | 0.5604          | 0.2449 | 0.0863 |
| 0.3312        | 7.0   | 4970  | 0.6122          | 0.3529 | 0.1307 |
| 0.3306        | 8.0   | 5680  | 0.5529          | 0.2572 | 0.0931 |
| 0.2915        | 9.0   | 6390  | 0.6499          | 0.2584 | 0.0929 |
| 0.2828        | 10.0  | 7100  | 0.6233          | 0.2678 | 0.0954 |
| 0.2664        | 11.0  | 7810  | 0.6266          | 0.2567 | 0.0904 |
| 0.2473        | 12.0  | 8520  | 0.6285          | 0.2561 | 0.0894 |
| 0.2289        | 13.0  | 9230  | 0.6137          | 0.2531 | 0.0901 |
| 0.2102        | 14.0  | 9940  | 0.6440          | 0.2483 | 0.0891 |
| 0.1976        | 15.0  | 10650 | 0.7161          | 0.2724 | 0.0957 |
| 0.1971        | 16.0  | 11360 | 0.6790          | 0.2525 | 0.0897 |


### Framework versions

- Transformers 4.46.0
- Pytorch 2.1.0+cu118
- Datasets 3.0.2
- Tokenizers 0.20.1