---
library_name: transformers
license: cc-by-nc-4.0
base_model: facebook/mms-1b-all
tags:
- generated_from_trainer
datasets:
- fleurs
metrics:
- wer
model-index:
- name: mms-1b-all-lg-CV-Fleurs_filtered-100hrs-v1
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: fleurs
      type: fleurs
      config: lg_ug
      split: test
      args: lg_ug
    metrics:
    - name: Wer
      type: wer
      value: 0.4098153547133139
---

<!-- 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. -->

# mms-1b-all-lg-CV-Fleurs_filtered-100hrs-v1

This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the fleurs dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2897
- Wer: 0.4098
- Cer: 0.0743

## 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: 4
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 70
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    | Cer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|
| 0.3203        | 1.0   | 7125  | 0.3178          | 0.4156 | 0.0762 |
| 0.2149        | 2.0   | 14250 | 0.3008          | 0.4194 | 0.0759 |
| 0.2093        | 3.0   | 21375 | 0.3015          | 0.4017 | 0.0743 |
| 0.2064        | 4.0   | 28500 | 0.3043          | 0.4114 | 0.0745 |
| 0.2042        | 5.0   | 35625 | 0.2955          | 0.4069 | 0.0753 |
| 0.2022        | 6.0   | 42750 | 0.3009          | 0.4088 | 0.0750 |
| 0.1989        | 7.0   | 49875 | 0.3088          | 0.4092 | 0.0756 |
| 0.1983        | 8.0   | 57000 | 0.2980          | 0.4081 | 0.0754 |
| 0.1969        | 9.0   | 64125 | 0.2951          | 0.4040 | 0.0741 |
| 0.1957        | 10.0  | 71250 | 0.2899          | 0.4039 | 0.0745 |
| 0.1945        | 11.0  | 78375 | 0.2896          | 0.4083 | 0.0744 |
| 0.1936        | 12.0  | 85500 | 0.2931          | 0.4038 | 0.0743 |
| 0.1929        | 13.0  | 92625 | 0.2897          | 0.4098 | 0.0743 |


### Framework versions

- Transformers 4.46.2
- Pytorch 2.1.0+cu118
- Datasets 3.1.0
- Tokenizers 0.20.3