---
license: cc-by-nc-4.0
base_model: facebook/mms-1b-all
tags:
- generated_from_trainer
datasets:
- nena_speech_1_0_test
metrics:
- wer
model-index:
- name: wav2vec2-large-mms-1b-urmi-christian-nostress
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: nena_speech_1_0_test
      type: nena_speech_1_0_test
      config: urmi (christian)
      split: test
      args: urmi (christian)
    metrics:
    - name: Wer
      type: wer
      value: 0.944954128440367
---

<!-- 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-mms-1b-urmi-christian-nostress

This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the nena_speech_1_0_test dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6617
- Wer: 0.9450
- Cer: 0.1846

## 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    | Cer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 14.5154       | 0.78  | 25   | 10.7711         | 1.0    | 0.9743 |
| 7.3688        | 1.56  | 50   | 6.3951          | 1.0    | 0.9408 |
| 3.895         | 2.34  | 75   | 2.4755          | 1.0    | 0.7579 |
| 1.6699        | 3.12  | 100  | 0.8689          | 0.9725 | 0.2286 |
| 1.1293        | 3.91  | 125  | 0.7194          | 0.9633 | 0.1981 |
| 0.9637        | 4.69  | 150  | 0.6617          | 0.9450 | 0.1846 |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1