---
license: mit
tags:
- generated_from_trainer
metrics:
- wer
base_model: facebook/w2v-bert-2.0
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: 0.1642
- Wer: 0.1271

## 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    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 1.0788        | 0.46  | 600   | 0.3546          | 0.4640 |
| 0.1732        | 0.92  | 1200  | 0.2307          | 0.3431 |
| 0.1247        | 1.38  | 1800  | 0.2097          | 0.2916 |
| 0.1092        | 1.84  | 2400  | 0.2121          | 0.2742 |
| 0.0896        | 2.3   | 3000  | 0.1817          | 0.2565 |
| 0.0776        | 2.76  | 3600  | 0.1715          | 0.2249 |
| 0.0695        | 3.22  | 4200  | 0.1684          | 0.2142 |
| 0.0581        | 3.68  | 4800  | 0.1667          | 0.2050 |
| 0.0521        | 4.14  | 5400  | 0.1629          | 0.1876 |
| 0.0426        | 4.6   | 6000  | 0.1553          | 0.1819 |
| 0.0389        | 5.06  | 6600  | 0.1485          | 0.1692 |
| 0.03          | 5.52  | 7200  | 0.1388          | 0.1667 |
| 0.03          | 5.98  | 7800  | 0.1441          | 0.1607 |
| 0.0208        | 6.44  | 8400  | 0.1444          | 0.1520 |
| 0.0209        | 6.9   | 9000  | 0.1339          | 0.1498 |
| 0.0145        | 7.36  | 9600  | 0.1418          | 0.1403 |
| 0.013         | 7.82  | 10200 | 0.1387          | 0.1351 |
| 0.0103        | 8.28  | 10800 | 0.1504          | 0.1321 |
| 0.0079        | 8.74  | 11400 | 0.1593          | 0.1331 |
| 0.0066        | 9.2   | 12000 | 0.1551          | 0.1222 |
| 0.004         | 9.66  | 12600 | 0.1642          | 0.1271 |


### Framework versions

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