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---
library_name: transformers
license: cc-by-nc-4.0
base_model: facebook/mms-1b-all
tags:
- automatic-speech-recognition
- toigen
- mms
- generated_from_trainer
metrics:
- wer
model-index:
- name: mms-1b-toigen-balanced-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-toigen-balanced-model
This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the TOIGEN - TOI dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3740
- Wer: 0.3990
## 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 |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 7.7726 | 0.4464 | 100 | 3.8109 | 0.9938 |
| 2.5726 | 0.8929 | 200 | 0.8106 | 0.6167 |
| 0.7986 | 1.3393 | 300 | 0.5409 | 0.5258 |
| 0.6324 | 1.7857 | 400 | 0.5256 | 0.5054 |
| 0.603 | 2.2321 | 500 | 0.4854 | 0.4832 |
| 0.59 | 2.6786 | 600 | 0.4733 | 0.4846 |
| 0.5489 | 3.125 | 700 | 0.4440 | 0.4657 |
| 0.5173 | 3.5714 | 800 | 0.4322 | 0.4576 |
| 0.5315 | 4.0179 | 900 | 0.4286 | 0.4453 |
| 0.4912 | 4.4643 | 1000 | 0.4254 | 0.4458 |
| 0.4728 | 4.9107 | 1100 | 0.4346 | 0.4430 |
| 0.4989 | 5.3571 | 1200 | 0.4050 | 0.4292 |
| 0.4661 | 5.8036 | 1300 | 0.4019 | 0.4255 |
| 0.4755 | 6.25 | 1400 | 0.4129 | 0.4449 |
| 0.4603 | 6.6964 | 1500 | 0.4046 | 0.4255 |
| 0.4229 | 7.1429 | 1600 | 0.3939 | 0.4150 |
| 0.455 | 7.5893 | 1700 | 0.4133 | 0.4155 |
| 0.4501 | 8.0357 | 1800 | 0.3978 | 0.4065 |
| 0.45 | 8.4821 | 1900 | 0.3925 | 0.4231 |
| 0.4226 | 8.9286 | 2000 | 0.3901 | 0.4098 |
| 0.3973 | 9.375 | 2100 | 0.3810 | 0.4056 |
| 0.4038 | 9.8214 | 2200 | 0.4178 | 0.4117 |
| 0.4559 | 10.2679 | 2300 | 0.3875 | 0.4075 |
| 0.4399 | 10.7143 | 2400 | 0.3742 | 0.3990 |
| 0.3545 | 11.1607 | 2500 | 0.3818 | 0.4013 |
| 0.4452 | 11.6071 | 2600 | 0.3906 | 0.3980 |
| 0.4014 | 12.0536 | 2700 | 0.3752 | 0.3999 |
### Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
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