---
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: tun_msa_wav2vec3
  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. -->

# tun_msa_wav2vec3

This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5827
- Wer: 0.5757
- Cer: 0.1836

## 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: 1e-06
- train_batch_size: 16
- 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: 700
- num_epochs: 50

### Training results

| Training Loss | Epoch   | Step  | Validation Loss | Wer    | Cer    |
|:-------------:|:-------:|:-----:|:---------------:|:------:|:------:|
| 5.268         | 2.9221  | 900   | 2.2839          | 1.0005 | 0.5919 |
| 2.0283        | 5.8442  | 1800  | 0.9714          | 0.6901 | 0.2320 |
| 1.4551        | 8.7662  | 2700  | 0.7691          | 0.6608 | 0.2154 |
| 1.2854        | 11.6883 | 3600  | 0.7028          | 0.6369 | 0.2057 |
| 1.1381        | 14.6104 | 4500  | 0.6529          | 0.6172 | 0.1991 |
| 1.1017        | 17.5325 | 5400  | 0.6325          | 0.6050 | 0.1952 |
| 1.0674        | 20.4545 | 6300  | 0.6189          | 0.5958 | 0.1914 |
| 0.9982        | 23.3766 | 7200  | 0.6089          | 0.5918 | 0.1895 |
| 0.9585        | 26.2987 | 8100  | 0.5986          | 0.5860 | 0.1877 |
| 0.9073        | 29.2208 | 9000  | 0.5948          | 0.5822 | 0.1866 |
| 0.91          | 32.1429 | 9900  | 0.5915          | 0.5804 | 0.1854 |
| 0.8775        | 35.0649 | 10800 | 0.5885          | 0.5787 | 0.1849 |
| 0.8973        | 37.9870 | 11700 | 0.5877          | 0.5775 | 0.1844 |
| 0.8908        | 40.9091 | 12600 | 0.5857          | 0.5763 | 0.1841 |
| 0.8503        | 43.8312 | 13500 | 0.5831          | 0.5764 | 0.1837 |
| 0.8843        | 46.7532 | 14400 | 0.5831          | 0.5765 | 0.1838 |
| 0.8554        | 49.6753 | 15300 | 0.5827          | 0.5757 | 0.1836 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1