transformers tensorboard safetensors wav2vec2 automatic-speech-recognition generated_from_trainer dataset:common_voice_11_0 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:
- common_voice_11_0
metrics:
- wer
model-index:
- name: model_mms
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_11_0
      type: common_voice_11_0
      config: tr
      split: test[:100]
      args: tr
    metrics:
    - name: Wer
      type: wer
      value: 0.3283018867924528
---

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

This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the common_voice_11_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2666
- Wer: 0.3283

## 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: 1
- num_epochs: 1
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 3.0741        | 0.12  | 100  | 0.3252          | 0.3698 |
| 0.2837        | 0.24  | 200  | 0.2980          | 0.3509 |
| 0.2725        | 0.36  | 300  | 0.2808          | 0.3566 |
| 0.2727        | 0.47  | 400  | 0.2893          | 0.3509 |
| 0.2721        | 0.59  | 500  | 0.2806          | 0.3377 |
| 0.2602        | 0.71  | 600  | 0.2832          | 0.3377 |
| 0.2631        | 0.83  | 700  | 0.2740          | 0.3396 |
| 0.2528        | 0.95  | 800  | 0.2666          | 0.3283 |


### Framework versions

- Transformers 4.37.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
