---
library_name: transformers
license: mit
base_model: facebook/w2v-bert-2.0
tags:
- automatic-speech-recognition
- BembaSpeech
- generated_from_trainer
metrics:
- wer
model-index:
- name: w2v-bert-bem-bembaspeech-model
  results: []
---

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

This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on the BEMBASPEECH - BEM dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2620
- Wer: 0.5353

## 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: 0.0003
- train_batch_size: 8
- eval_batch_size: 8
- 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: 100
- num_epochs: 30.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 0.7066        | 0.2811 | 200  | 0.5066          | 0.7648 |
| 0.5538        | 0.5622 | 400  | 0.4313          | 0.7232 |
| 0.4574        | 0.8433 | 600  | 0.4102          | 0.6956 |
| 0.4084        | 1.1244 | 800  | 0.3529          | 0.6276 |
| 0.388         | 1.4055 | 1000 | 0.3004          | 0.5724 |
| 0.3803        | 1.6866 | 1200 | 0.3376          | 0.6477 |
| 0.367         | 1.9677 | 1400 | 0.2911          | 0.5802 |
| 0.3168        | 2.2488 | 1600 | 0.3106          | 0.5725 |
| 0.3227        | 2.5299 | 1800 | 0.2654          | 0.5348 |
| 0.3111        | 2.8110 | 2000 | 0.2621          | 0.5494 |
| 0.2823        | 3.0921 | 2200 | 0.2665          | 0.5422 |
| 0.2603        | 3.3732 | 2400 | 0.2623          | 0.5174 |
| 0.2735        | 3.6543 | 2600 | 0.2620          | 0.5353 |
| 0.2666        | 3.9353 | 2800 | 0.2753          | 0.5450 |
| 0.2248        | 4.2164 | 3000 | 0.2881          | 0.5818 |
| 0.2408        | 4.4975 | 3200 | 0.2748          | 0.5324 |


### Framework versions

- Transformers 4.46.0.dev0
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0