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---
library_name: transformers
license: cc-by-nc-4.0
base_model: mms-meta/mms-zeroshot-300m
tags:
- automatic-speech-recognition
- BembaSpeech
- mms
- generated_from_trainer
metrics:
- wer
model-index:
- name: mms-zeroshot-bem-sv-male
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-zeroshot-bem-sv-male
This model is a fine-tuned version of [mms-meta/mms-zeroshot-300m](https://huggingface.co/mms-meta/mms-zeroshot-300m) on the BEMBASPEECH - BEM dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1874
- Wer: 0.3949
## 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: 8
- 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: 100
- num_epochs: 10.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:------:|
| No log | 0.2183 | 200 | 2.3822 | 1.0 |
| No log | 0.4367 | 400 | 0.2715 | 0.5093 |
| 2.7769 | 0.6550 | 600 | 0.2489 | 0.4820 |
| 2.7769 | 0.8734 | 800 | 0.2296 | 0.4695 |
| 0.6809 | 1.0917 | 1000 | 0.2209 | 0.4638 |
| 0.6809 | 1.3100 | 1200 | 0.2163 | 0.4469 |
| 0.6809 | 1.5284 | 1400 | 0.2092 | 0.4400 |
| 0.6113 | 1.7467 | 1600 | 0.2047 | 0.4346 |
| 0.6113 | 1.9651 | 1800 | 0.2074 | 0.4467 |
| 0.5974 | 2.1834 | 2000 | 0.2041 | 0.4304 |
| 0.5974 | 2.4017 | 2200 | 0.2054 | 0.4317 |
| 0.5974 | 2.6201 | 2400 | 0.1987 | 0.4240 |
| 0.5636 | 2.8384 | 2600 | 0.2003 | 0.4252 |
| 0.5636 | 3.0568 | 2800 | 0.1997 | 0.4287 |
| 0.5398 | 3.2751 | 3000 | 0.2097 | 0.4400 |
| 0.5398 | 3.4934 | 3200 | 0.1968 | 0.4165 |
| 0.5398 | 3.7118 | 3400 | 0.2013 | 0.4218 |
| 0.5334 | 3.9301 | 3600 | 0.2003 | 0.4230 |
| 0.5334 | 4.1485 | 3800 | 0.1976 | 0.4227 |
| 0.5123 | 4.3668 | 4000 | 0.1978 | 0.4198 |
| 0.5123 | 4.5852 | 4200 | 0.2019 | 0.4298 |
| 0.5123 | 4.8035 | 4400 | 0.1939 | 0.4146 |
| 0.5119 | 5.0218 | 4600 | 0.1989 | 0.4161 |
| 0.5119 | 5.2402 | 4800 | 0.1902 | 0.4076 |
| 0.4929 | 5.4585 | 5000 | 0.1929 | 0.4116 |
| 0.4929 | 5.6769 | 5200 | 0.1943 | 0.4144 |
| 0.4929 | 5.8952 | 5400 | 0.1922 | 0.4106 |
| 0.4878 | 6.1135 | 5600 | 0.1933 | 0.4137 |
| 0.4878 | 6.3319 | 5800 | 0.1920 | 0.4058 |
| 0.4755 | 6.5502 | 6000 | 0.1927 | 0.4171 |
| 0.4755 | 6.7686 | 6200 | 0.1920 | 0.4127 |
| 0.4755 | 6.9869 | 6400 | 0.1925 | 0.4061 |
| 0.475 | 7.2052 | 6600 | 0.1884 | 0.4058 |
| 0.475 | 7.4236 | 6800 | 0.1903 | 0.4070 |
| 0.4715 | 7.6419 | 7000 | 0.1882 | 0.3996 |
| 0.4715 | 7.8603 | 7200 | 0.1881 | 0.4033 |
| 0.4715 | 8.0786 | 7400 | 0.1885 | 0.4007 |
| 0.4575 | 8.2969 | 7600 | 0.1885 | 0.4016 |
| 0.4575 | 8.5153 | 7800 | 0.1888 | 0.4050 |
| 0.4611 | 8.7336 | 8000 | 0.1884 | 0.4046 |
| 0.4611 | 8.9520 | 8200 | 0.1881 | 0.3974 |
| 0.4611 | 9.1703 | 8400 | 0.1865 | 0.3956 |
| 0.4559 | 9.3886 | 8600 | 0.1875 | 0.3974 |
| 0.4559 | 9.6070 | 8800 | 0.1872 | 0.3996 |
| 0.4536 | 9.8253 | 9000 | 0.1876 | 0.3953 |
### Framework versions
- Transformers 4.45.0.dev0
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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