---
library_name: transformers
license: mit
base_model: facebook/w2v-bert-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: w2v-bert-cv-grain-lg_both_v2
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# w2v-bert-cv-grain-lg_both_v2

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: 0.0892
- Wer: 0.0443
- Cer: 0.0123

## 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: 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
- num_epochs: 80
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Wer    | Cer    |
|:-------------:|:-----:|:------:|:---------------:|:------:|:------:|
| 0.2889        | 1.0   | 10812  | 0.1708          | 0.1703 | 0.0386 |
| 0.1849        | 2.0   | 21624  | 0.1342          | 0.1274 | 0.0285 |
| 0.1512        | 3.0   | 32436  | 0.1144          | 0.1044 | 0.0244 |
| 0.1313        | 4.0   | 43248  | 0.1033          | 0.0918 | 0.0217 |
| 0.117         | 5.0   | 54060  | 0.1034          | 0.0738 | 0.0191 |
| 0.1056        | 6.0   | 64872  | 0.0906          | 0.0738 | 0.0181 |
| 0.0962        | 7.0   | 75684  | 0.0959          | 0.0655 | 0.0168 |
| 0.0885        | 8.0   | 86496  | 0.0860          | 0.0592 | 0.0155 |
| 0.0807        | 9.0   | 97308  | 0.0844          | 0.0603 | 0.0154 |
| 0.0742        | 10.0  | 108120 | 0.0814          | 0.0573 | 0.0144 |
| 0.0683        | 11.0  | 118932 | 0.0858          | 0.0588 | 0.0154 |
| 0.0629        | 12.0  | 129744 | 0.0944          | 0.0538 | 0.0146 |
| 0.0581        | 13.0  | 140556 | 0.0842          | 0.0558 | 0.0151 |
| 0.0528        | 14.0  | 151368 | 0.0873          | 0.0503 | 0.0141 |
| 0.0479        | 15.0  | 162180 | 0.0820          | 0.0503 | 0.0138 |
| 0.0429        | 16.0  | 172992 | 0.0815          | 0.0427 | 0.0125 |
| 0.0392        | 17.0  | 183804 | 0.0864          | 0.0466 | 0.0128 |
| 0.035         | 18.0  | 194616 | 0.0899          | 0.0479 | 0.0128 |
| 0.0316        | 19.0  | 205428 | 0.0872          | 0.0430 | 0.0120 |
| 0.0286        | 20.0  | 216240 | 0.0821          | 0.0425 | 0.0114 |
| 0.0254        | 21.0  | 227052 | 0.0898          | 0.0466 | 0.0122 |
| 0.0229        | 22.0  | 237864 | 0.0864          | 0.0417 | 0.0120 |
| 0.021         | 23.0  | 248676 | 0.0893          | 0.0408 | 0.0122 |
| 0.0192        | 24.0  | 259488 | 0.0878          | 0.0430 | 0.0118 |
| 0.0171        | 25.0  | 270300 | 0.0994          | 0.0473 | 0.0128 |
| 0.0156        | 26.0  | 281112 | 0.0892          | 0.0443 | 0.0123 |


### Framework versions

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