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

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# w2v-bert-bem-genbed-m-model

This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on the GENBED - BEM dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4168
- Wer: 0.5478

## 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    |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 0.7215        | 1.1019  | 200  | 0.6150          | 0.7430 |
| 0.5519        | 2.2039  | 400  | 0.5605          | 0.7116 |
| 0.4346        | 3.3058  | 600  | 0.4709          | 0.6378 |
| 0.3545        | 4.4077  | 800  | 0.4686          | 0.5984 |
| 0.3004        | 5.5096  | 1000 | 0.4578          | 0.6203 |
| 0.2498        | 6.6116  | 1200 | 0.4245          | 0.5246 |
| 0.23          | 7.7135  | 1400 | 0.4168          | 0.5478 |
| 0.1959        | 8.8154  | 1600 | 0.4212          | 0.5230 |
| 0.1682        | 9.9174  | 1800 | 0.4357          | 0.5054 |
| 0.1459        | 11.0193 | 2000 | 0.4253          | 0.5296 |


### Framework versions

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