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---
library_name: transformers
license: cc-by-nc-4.0
base_model: facebook/mms-1b-all
tags:
- automatic-speech-recognition
- genbed
- mms
- generated_from_trainer
metrics:
- wer
model-index:
- name: mms-1b-nyagen-combined-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-nyagen-combined-model
This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the GENBED - BEM dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1727
- Wer: 0.2465
## 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 |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 6.9978 | 0.1364 | 100 | 0.6384 | 0.5015 |
| 0.482 | 0.2729 | 200 | 0.2777 | 0.3713 |
| 0.3907 | 0.4093 | 300 | 0.2484 | 0.3481 |
| 0.3782 | 0.5457 | 400 | 0.2290 | 0.3232 |
| 0.3316 | 0.6821 | 500 | 0.2222 | 0.3148 |
| 0.3158 | 0.8186 | 600 | 0.2127 | 0.3042 |
| 0.3199 | 0.9550 | 700 | 0.2106 | 0.2932 |
| 0.3223 | 1.0914 | 800 | 0.2013 | 0.2826 |
| 0.3075 | 1.2278 | 900 | 0.1975 | 0.2709 |
| 0.3015 | 1.3643 | 1000 | 0.1942 | 0.2762 |
| 0.3049 | 1.5007 | 1100 | 0.1895 | 0.2729 |
| 0.3029 | 1.6371 | 1200 | 0.1888 | 0.2718 |
| 0.2626 | 1.7735 | 1300 | 0.1866 | 0.2683 |
| 0.2803 | 1.9100 | 1400 | 0.1830 | 0.2615 |
| 0.2725 | 2.0464 | 1500 | 0.1814 | 0.2626 |
| 0.2732 | 2.1828 | 1600 | 0.1783 | 0.2641 |
| 0.249 | 2.3192 | 1700 | 0.1828 | 0.2560 |
| 0.2423 | 2.4557 | 1800 | 0.1762 | 0.2480 |
| 0.2668 | 2.5921 | 1900 | 0.1732 | 0.2458 |
| 0.2653 | 2.7285 | 2000 | 0.1727 | 0.2460 |
| 0.2614 | 2.8649 | 2100 | 0.1749 | 0.2533 |
| 0.2474 | 3.0014 | 2200 | 0.1733 | 0.2438 |
| 0.2317 | 3.1378 | 2300 | 0.1767 | 0.2447 |
### Framework versions
- Transformers 4.48.0.dev0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
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