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---
library_name: transformers
license: cc-by-nc-4.0
base_model: facebook/mms-1b-all
tags:
- automatic-speech-recognition
- lozgen
- mms
- generated_from_trainer
metrics:
- wer
model-index:
- name: mms-1b-lozgen-male-model
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. -->
# mms-1b-lozgen-male-model
This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the LOZGEN - LOZ dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3107
- Wer: 0.3264
## 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: 0.0003
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- 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
- lr_scheduler_warmup_steps: 100
- num_epochs: 30.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 6.7665 | 0.7634 | 100 | 3.1610 | 0.9990 |
| 2.6476 | 1.5267 | 200 | 2.2410 | 0.8953 |
| 1.5694 | 2.2901 | 300 | 0.5585 | 0.7599 |
| 0.6761 | 3.0534 | 400 | 0.4566 | 0.6319 |
| 0.5793 | 3.8168 | 500 | 0.4013 | 0.4822 |
| 0.5392 | 4.5802 | 600 | 0.3795 | 0.4554 |
| 0.4809 | 5.3435 | 700 | 0.3730 | 0.4333 |
| 0.4813 | 6.1069 | 800 | 0.3597 | 0.4230 |
| 0.4484 | 6.8702 | 900 | 0.3432 | 0.3925 |
| 0.4418 | 7.6336 | 1000 | 0.3391 | 0.3947 |
| 0.4322 | 8.3969 | 1100 | 0.3339 | 0.3841 |
| 0.3963 | 9.1603 | 1200 | 0.3294 | 0.3669 |
| 0.4104 | 9.9237 | 1300 | 0.3217 | 0.3635 |
| 0.3777 | 10.6870 | 1400 | 0.3177 | 0.3610 |
| 0.3785 | 11.4504 | 1500 | 0.3236 | 0.3539 |
| 0.3682 | 12.2137 | 1600 | 0.3144 | 0.3468 |
| 0.3654 | 12.9771 | 1700 | 0.3122 | 0.3529 |
| 0.3509 | 13.7405 | 1800 | 0.3088 | 0.3463 |
| 0.3412 | 14.5038 | 1900 | 0.3146 | 0.3347 |
| 0.3344 | 15.2672 | 2000 | 0.3108 | 0.3416 |
| 0.3351 | 16.0305 | 2100 | 0.3107 | 0.3264 |
### Framework versions
- Transformers 4.48.0.dev0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
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