---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice_11_0
metrics:
- wer
model-index:
- name: p4b/whisper-large-v2-lv
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_11_0
      type: common_voice_11_0
      config: lv
      split: test
      args: lv
    metrics:
    - name: Wer
      type: wer
      value: 19.97153700189753
---

<!-- 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. -->

# p4b/whisper-large-v2-lv

This model is a fine-tuned version of [p4b/whisper-large-v2-lv](https://huggingface.co/p4b/whisper-large-v2-lv) on the common_voice_11_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2593
- Wer: 19.9715

## 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: 1e-07
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- training_steps: 900

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.7919        | 3.03  | 200  | 0.2793          | 22.5806 |
| 0.4409        | 6.05  | 400  | 0.2651          | 20.6072 |
| 0.4393        | 10.01 | 600  | 0.2600          | 20.0664 |
| 0.4975        | 13.04 | 800  | 0.2593          | 19.9715 |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 2.0.0.dev20221218+cu116
- Datasets 2.7.1
- Tokenizers 0.13.2