---
license: mit
base_model: facebook/w2v-bert-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: w2v-bert-2.0-nonstudio_and_studioRecords
  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-nonstudio_and_studioRecords

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: 0.1641
- Wer: 0.1184

## 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: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- 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 | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 1.1077        | 0.46  | 600   | 0.4029          | 0.4897 |
| 0.1727        | 0.92  | 1200  | 0.2339          | 0.3573 |
| 0.1224        | 1.38  | 1800  | 0.2159          | 0.3225 |
| 0.1103        | 1.84  | 2400  | 0.1838          | 0.2764 |
| 0.0907        | 2.3   | 3000  | 0.1844          | 0.2603 |
| 0.0796        | 2.76  | 3600  | 0.1829          | 0.2498 |
| 0.0685        | 3.22  | 4200  | 0.1719          | 0.2336 |
| 0.0588        | 3.68  | 4800  | 0.1607          | 0.2030 |
| 0.054         | 4.14  | 5400  | 0.1611          | 0.1941 |
| 0.0424        | 4.6   | 6000  | 0.1536          | 0.1821 |
| 0.0402        | 5.06  | 6600  | 0.1562          | 0.1769 |
| 0.0312        | 5.52  | 7200  | 0.1494          | 0.1655 |
| 0.0303        | 5.98  | 7800  | 0.1471          | 0.1510 |
| 0.0218        | 6.44  | 8400  | 0.1707          | 0.1488 |
| 0.0218        | 6.9   | 9000  | 0.1458          | 0.1296 |
| 0.0151        | 7.36  | 9600  | 0.1424          | 0.1326 |
| 0.014         | 7.82  | 10200 | 0.1406          | 0.1266 |
| 0.0107        | 8.28  | 10800 | 0.1476          | 0.1291 |
| 0.0078        | 8.74  | 11400 | 0.1563          | 0.1254 |
| 0.007         | 9.2   | 12000 | 0.1528          | 0.1197 |
| 0.0041        | 9.66  | 12600 | 0.1641          | 0.1184 |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.1.1+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1