---
library_name: transformers
license: mit
base_model: facebook/w2v-bert-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: W2V2_Bert_BIG-C_BEMBA_10hr_v1
  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. -->

# W2V2_Bert_BIG-C_BEMBA_10hr_v1

This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co./facebook/w2v-bert-2.0) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: inf
- Wer: 0.4556
- Cer: 0.1168

## 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: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 100
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer    | Cer    |
|:-------------:|:-------:|:----:|:---------------:|:------:|:------:|
| 2.809         | 0.9992  | 160  | 1.1132          | 0.6643 | 0.2005 |
| 0.9734        | 1.9984  | 320  | 0.9685          | 0.5738 | 0.1782 |
| 0.8447        | 2.9977  | 480  | 0.8472          | 0.5473 | 0.1643 |
| 0.8229        | 3.9969  | 640  | 0.8477          | 0.5224 | 0.1630 |
| 0.8776        | 4.9961  | 800  | 0.9532          | 0.5940 | 0.1767 |
| 1.1449        | 5.9953  | 960  | 1.7822          | 0.9266 | 0.3271 |
| 3.2265        | 6.9945  | 1120 | 3.3887          | 0.9994 | 0.9847 |
| 3.5702        | 8.0     | 1281 | 2.9517          | 0.9993 | 0.9694 |
| 3.92          | 8.9992  | 1441 | 4.2453          | 1.0    | 1.0    |
| 3.9997        | 9.9984  | 1601 | 4.4161          | 1.0    | 1.0    |
| 4.004         | 10.9977 | 1761 | 4.4161          | 1.0    | 1.0    |
| 3.9971        | 11.9969 | 1921 | 4.4161          | 1.0    | 1.0    |
| 4.0026        | 12.9961 | 2081 | 4.4161          | 1.0    | 1.0    |
| 4.002         | 13.9953 | 2241 | 4.4161          | 1.0    | 1.0    |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.2.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1