transformers pytorch wav2vec2 automatic-speech-recognition generated_from_trainer dataset:audiofolder base_model:facebook/mms-1b-all license:cc-by-nc-4.0 model-index endpoints_compatible region:us
---
license: cc-by-nc-4.0
base_model: facebook/mms-1b-all
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- wer
model-index:
- name: finetune_out
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: audiofolder
      type: audiofolder
      config: ay
      split: train
      args: ay
    metrics:
    - name: Wer
      type: wer
      value: 1.0
---

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# finetune_out

This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the audiofolder dataset.
It achieves the following results on the evaluation set:
- Loss: 16.0915
- 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: 0.001
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 4

### Training results



### Framework versions

- Transformers 4.33.1
- Pytorch 2.0.1
- Datasets 2.13.0
- Tokenizers 0.13.3
