---
license: apache-2.0
base_model: facebook/wav2vec2-large
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-large-sw-cv-100hr-v6
  results: []
---

<!-- 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-large-sw-cv-100hr-v6

This model is a fine-tuned version of [facebook/wav2vec2-large](https://huggingface.co/facebook/wav2vec2-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6098
- Model Preparation Time: 0.0065
- Wer: 0.3875
- Cer: 0.1346

## 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: 0.001
- train_batch_size: 64
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.2
- num_epochs: 100
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Cer    | Validation Loss | Model Preparation Time | Wer    |
|:-------------:|:-----:|:-----:|:------:|:---------------:|:----------------------:|:------:|
| 2.1201        | 1.0   | 1040  | 0.1472 | 0.6354          | 0.0059                 | 0.5377 |
| 0.4194        | 2.0   | 2080  | 0.1104 | 0.4653          | 0.0059                 | 0.4050 |
| 0.3266        | 3.0   | 3120  | 0.1087 | 0.3807          | 0.0059                 | 0.3726 |
| 0.2997        | 4.0   | 4160  | 0.0944 | 0.3834          | 0.0059                 | 0.3445 |
| 0.2984        | 5.0   | 5200  | 0.0979 | 0.4147          | 0.0059                 | 0.3493 |
| 0.3072        | 6.0   | 6240  | 0.1020 | 0.4111          | 0.0059                 | 0.3583 |
| 0.3265        | 7.0   | 7280  | 0.1147 | 0.4162          | 0.0059                 | 0.3947 |
| 0.3477        | 8.0   | 8320  | 0.4503 | 0.0065          | 0.3979                 | 0.1191 |
| 0.384         | 9.0   | 9360  | 0.5286 | 0.0065          | 0.4552                 | 0.1442 |
| 0.4269        | 10.0  | 10400 | 0.5312 | 0.0065          | 0.4761                 | 0.1471 |
| 1.5371        | 11.0  | 11440 | 4.5667 | 0.0065          | 0.9999                 | 0.9827 |
| 4.5758        | 12.0  | 12480 | 4.5229 | 0.0065          | 0.9999                 | 0.9827 |
| 4.5739        | 13.0  | 13520 | 4.5302 | 0.0065          | 0.9999                 | 0.9827 |
| 4.5753        | 14.0  | 14560 | 4.5329 | 0.0065          | 0.9999                 | 0.9827 |
| 4.5736        | 15.0  | 15600 | 4.5338 | 0.0065          | 0.9999                 | 0.9827 |
| 4.5724        | 16.0  | 16640 | 4.5463 | 0.0065          | 0.9999                 | 0.9827 |
| 4.5738        | 17.0  | 17680 | 4.5220 | 0.0065          | 0.9999                 | 0.9827 |


### Framework versions

- Transformers 4.44.0
- Pytorch 2.1.0+cu118
- Datasets 2.20.0
- Tokenizers 0.19.1