---
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: 0.1629
- Wer: 0.1284

## 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    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 1.1293        | 0.46  | 600   | 0.3873          | 0.4777 |
| 0.1724        | 0.92  | 1200  | 0.2435          | 0.3533 |
| 0.1229        | 1.38  | 1800  | 0.2188          | 0.2971 |
| 0.109         | 1.84  | 2400  | 0.2135          | 0.2647 |
| 0.0895        | 2.3   | 3000  | 0.1911          | 0.2441 |
| 0.0779        | 2.76  | 3600  | 0.1738          | 0.2389 |
| 0.0682        | 3.22  | 4200  | 0.1876          | 0.2476 |
| 0.0568        | 3.68  | 4800  | 0.1603          | 0.2140 |
| 0.0527        | 4.14  | 5400  | 0.1697          | 0.1809 |
| 0.0422        | 4.6   | 6000  | 0.1656          | 0.1876 |
| 0.0393        | 5.06  | 6600  | 0.1600          | 0.1732 |
| 0.0311        | 5.52  | 7200  | 0.1522          | 0.1585 |
| 0.0291        | 5.98  | 7800  | 0.1483          | 0.1543 |
| 0.0207        | 6.44  | 8400  | 0.1561          | 0.1483 |
| 0.0208        | 6.9   | 9000  | 0.1502          | 0.1391 |
| 0.0151        | 7.36  | 9600  | 0.1561          | 0.1408 |
| 0.0138        | 7.82  | 10200 | 0.1491          | 0.1296 |
| 0.0108        | 8.28  | 10800 | 0.1472          | 0.1257 |
| 0.008         | 8.74  | 11400 | 0.1658          | 0.1252 |
| 0.0065        | 9.2   | 12000 | 0.1665          | 0.1227 |
| 0.0045        | 9.66  | 12600 | 0.1629          | 0.1284 |


### Framework versions

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