---
license: apache-2.0
tags:
- generated_from_trainer
base_model: facebook/wav2vec2-base
datasets:
- transcribed_calls
metrics:
- wer
model-index:
- name: wav2vec2-base-wonders-phonemes
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: transcribed_calls
      type: transcribed_calls
      config: default
      split: None
      args: default
    metrics:
    - type: wer
      value: 1.0
      name: Wer
---

<!-- 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. -->

# wav2vec2-base-wonders-phonemes

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the transcribed_calls dataset.
It achieves the following results on the evaluation set:
- Loss: 4.1008
- Wer: 1.0

## 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: 0.0001
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:---------------:|:---:|
| 3.5174        | 0.73  | 2000  | 4.1615          | 1.0 |
| 3.3943        | 1.45  | 4000  | 4.2182          | 1.0 |
| 3.3465        | 2.18  | 6000  | 4.2119          | 1.0 |
| 3.3343        | 2.9   | 8000  | 4.2471          | 1.0 |
| 3.3546        | 3.63  | 10000 | 4.0944          | 1.0 |
| 3.7063        | 4.36  | 12000 | 4.1280          | 1.0 |
| 3.352         | 5.08  | 14000 | 4.0348          | 1.0 |
| 3.4307        | 5.81  | 16000 | 4.1120          | 1.0 |
| 3.3496        | 6.54  | 18000 | 4.0892          | 1.0 |
| 3.3681        | 7.26  | 20000 | 4.1087          | 1.0 |
| 3.3285        | 7.99  | 22000 | 4.0877          | 1.0 |
| 3.4597        | 8.71  | 24000 | 4.1041          | 1.0 |
| 3.3582        | 9.44  | 26000 | 4.0729          | 1.0 |
| 3.3898        | 10.17 | 28000 | 4.0884          | 1.0 |
| 3.4005        | 10.89 | 30000 | 4.1275          | 1.0 |
| 3.3362        | 11.62 | 32000 | 4.0973          | 1.0 |
| 3.4801        | 12.35 | 34000 | 4.0916          | 1.0 |
| 3.3902        | 13.07 | 36000 | 4.0946          | 1.0 |
| 3.3554        | 13.8  | 38000 | 4.1222          | 1.0 |
| 3.5212        | 14.52 | 40000 | 4.0763          | 1.0 |
| 3.3771        | 15.25 | 42000 | 4.1347          | 1.0 |
| 3.333         | 15.98 | 44000 | 4.1217          | 1.0 |
| 3.3605        | 16.7  | 46000 | 4.1400          | 1.0 |
| 3.3526        | 17.43 | 48000 | 4.1099          | 1.0 |
| 3.3134        | 18.16 | 50000 | 4.1327          | 1.0 |
| 3.5681        | 18.88 | 52000 | 4.1114          | 1.0 |
| 3.3497        | 19.61 | 54000 | 4.1006          | 1.0 |
| 4.0995        | 20.33 | 56000 | 4.0972          | 1.0 |
| 3.3377        | 21.06 | 58000 | 4.1035          | 1.0 |
| 3.355         | 21.79 | 60000 | 4.1022          | 1.0 |
| 3.5084        | 22.51 | 62000 | 4.1252          | 1.0 |
| 3.3558        | 23.24 | 64000 | 4.1028          | 1.0 |
| 3.3328        | 23.97 | 66000 | 4.0976          | 1.0 |
| 3.8824        | 24.69 | 68000 | 4.1290          | 1.0 |
| 3.3406        | 25.42 | 70000 | 4.1173          | 1.0 |
| 3.9972        | 26.14 | 72000 | 4.1178          | 1.0 |
| 3.4915        | 26.87 | 74000 | 4.0926          | 1.0 |
| 3.5408        | 27.6  | 76000 | 4.1069          | 1.0 |
| 3.6864        | 28.32 | 78000 | 4.1030          | 1.0 |
| 3.326         | 29.05 | 80000 | 4.1058          | 1.0 |
| 3.3171        | 29.77 | 82000 | 4.1008          | 1.0 |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.3.0.dev20240314+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2