---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- wer
model-index:
- name: w2v2-lmk_augmented
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: audiofolder
      type: audiofolder
      config: default
      split: test
      args: default
    metrics:
    - name: Wer
      type: wer
      value: 0.4878048780487805
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# w2v2-lmk_augmented

This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the audiofolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2406
- Wer: 0.4878
- Cer: 0.1858

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 300
- num_epochs: 100
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer    | Cer    |
|:-------------:|:-------:|:----:|:---------------:|:------:|:------:|
| 8.5498        | 2.7123  | 100  | 4.0528          | 1.0    | 1.0    |
| 3.1716        | 5.4110  | 200  | 2.9634          | 1.0    | 1.0    |
| 2.9756        | 8.1096  | 300  | 2.8924          | 1.0    | 1.0    |
| 2.8279        | 10.8219 | 400  | 2.5968          | 1.0    | 1.0    |
| 2.2866        | 13.5205 | 500  | 1.7827          | 0.9895 | 0.6283 |
| 1.619         | 16.2192 | 600  | 1.3242          | 0.9443 | 0.4021 |
| 1.2926        | 18.9315 | 700  | 1.1299          | 0.7875 | 0.2833 |
| 1.0181        | 21.6301 | 800  | 1.1390          | 0.6585 | 0.2513 |
| 0.8774        | 24.3288 | 900  | 1.0760          | 0.6132 | 0.2338 |
| 0.7471        | 27.0274 | 1000 | 0.9959          | 0.5889 | 0.2155 |
| 0.6542        | 29.7397 | 1100 | 1.0575          | 0.5575 | 0.2117 |
| 0.5632        | 32.4384 | 1200 | 1.0240          | 0.5784 | 0.2171 |
| 0.4834        | 35.1370 | 1300 | 1.0971          | 0.5505 | 0.1912 |
| 0.4716        | 37.8493 | 1400 | 1.1336          | 0.5749 | 0.2056 |
| 0.45          | 40.5479 | 1500 | 1.0703          | 0.5679 | 0.2079 |
| 0.394         | 43.2466 | 1600 | 1.1579          | 0.5645 | 0.2178 |
| 0.3588        | 45.9589 | 1700 | 1.0555          | 0.5296 | 0.1896 |
| 0.3217        | 48.6575 | 1800 | 1.2323          | 0.5575 | 0.2102 |
| 0.3245        | 51.3562 | 1900 | 1.1639          | 0.5401 | 0.2018 |
| 0.289         | 54.0548 | 2000 | 1.1304          | 0.5122 | 0.1927 |
| 0.28          | 56.7671 | 2100 | 1.2295          | 0.5296 | 0.2003 |
| 0.2521        | 59.4658 | 2200 | 1.1612          | 0.5226 | 0.1950 |
| 0.2624        | 62.1644 | 2300 | 1.1982          | 0.5157 | 0.2003 |
| 0.2402        | 64.8767 | 2400 | 1.2075          | 0.5296 | 0.1988 |
| 0.2258        | 67.5753 | 2500 | 1.2091          | 0.5366 | 0.2003 |
| 0.2232        | 70.2740 | 2600 | 1.1830          | 0.5296 | 0.1957 |
| 0.2181        | 72.9863 | 2700 | 1.2001          | 0.5157 | 0.1942 |
| 0.2214        | 75.6849 | 2800 | 1.1942          | 0.5052 | 0.1889 |
| 0.1752        | 78.3836 | 2900 | 1.1873          | 0.5087 | 0.1896 |
| 0.1891        | 81.0822 | 3000 | 1.2159          | 0.5192 | 0.1927 |
| 0.1733        | 83.7945 | 3100 | 1.2105          | 0.5017 | 0.1881 |
| 0.1982        | 86.4932 | 3200 | 1.2331          | 0.5087 | 0.1874 |
| 0.1681        | 89.1918 | 3300 | 1.1848          | 0.4808 | 0.1790 |
| 0.1631        | 91.9041 | 3400 | 1.2273          | 0.4878 | 0.1858 |
| 0.1579        | 94.6027 | 3500 | 1.2334          | 0.4948 | 0.1843 |
| 0.1795        | 97.3014 | 3600 | 1.2399          | 0.4878 | 0.1851 |
| 0.1592        | 100.0   | 3700 | 1.2406          | 0.4878 | 0.1858 |


### Framework versions

- Transformers 4.57.1
- Pytorch 2.8.0+cu128
- Datasets 3.0.0
- Tokenizers 0.22.1