---
base_model: ylacombe/w2v-bert-2.0
tags:
- generated_from_trainer
datasets:
- common_voice_16_0
model-index:
- name: w2v-bert-2.0-japanese-colab-CV16.0
  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-japanese-colab-CV16.0

This model is a fine-tuned version of [ylacombe/w2v-bert-2.0](https://huggingface.co/ylacombe/w2v-bert-2.0) on the common_voice_16_0 dataset.
It achieves the following results on the evaluation set:
- Loss: inf
- Cer: 0.3171

## 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: 1
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Cer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 4.2694        | 0.96  | 300  | inf             | 0.6823 |
| 2.0595        | 1.93  | 600  | inf             | 0.4528 |
| 1.3044        | 2.89  | 900  | inf             | 0.3920 |
| 1.0889        | 3.85  | 1200 | inf             | 0.3579 |
| 0.7867        | 4.82  | 1500 | inf             | 0.3518 |
| 0.4371        | 5.78  | 1800 | inf             | 0.3371 |
| 0.3414        | 6.74  | 2100 | inf             | 0.3246 |
| 0.2373        | 7.7   | 2400 | inf             | 0.3253 |
| 0.1171        | 8.67  | 2700 | inf             | 0.3183 |
| 0.0524        | 9.63  | 3000 | inf             | 0.3171 |


### Framework versions

- Transformers 4.37.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1