---
license: cc-by-nc-4.0
base_model: facebook/mms-1b-all
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-large-mms-1b-nya-colab
  results: []
---

<!-- 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-nya-colab

This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4327
- Wer: 0.3505

## 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: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 4.1659        | 0.2   | 200  | 0.6822          | 0.5353 |
| 0.2331        | 0.39  | 400  | 0.5220          | 0.4493 |
| 0.2119        | 0.59  | 600  | 0.4967          | 0.4146 |
| 0.1995        | 0.79  | 800  | 0.5021          | 0.4025 |
| 0.1812        | 0.99  | 1000 | 0.5046          | 0.3979 |
| 0.1744        | 1.18  | 1200 | 0.4786          | 0.3884 |
| 0.1783        | 1.38  | 1400 | 0.4630          | 0.3786 |
| 0.1663        | 1.58  | 1600 | 0.4511          | 0.3634 |
| 0.1609        | 1.77  | 1800 | 0.4656          | 0.3647 |
| 0.1632        | 1.97  | 2000 | 0.4254          | 0.3553 |
| 0.1568        | 2.17  | 2200 | 0.4326          | 0.3529 |
| 0.1544        | 2.37  | 2400 | 0.4291          | 0.3477 |
| 0.1524        | 2.56  | 2600 | 0.4327          | 0.3505 |


### Framework versions

- Transformers 4.31.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3