---
license: cc-by-nc-4.0
tags:
- generated_from_trainer
datasets:
- spgispeech_xs
base_model: facebook/mms-300m
model-index:
- name: wav2vec2-large-mms-300m-FULL-SPGI-xs
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: Test set for spgispeech
      type: kensho/spgispeech
      config: test
      split: test
    metrics:
    - type: wer
      value: 100.0
      name: WER
    - type: cer
      value: 99.3
      name: CER
---

<!-- 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-300m-FULL-SPGI-xs

This model is a fine-tuned version of [facebook/mms-300m](https://huggingface.co/facebook/mms-300m) on the spgispeech_xs dataset.

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 120
- mixed_precision_training: Native AMP

### Training results



### Framework versions

- Transformers 4.36.0.dev0
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0