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---
library_name: transformers
license: cc-by-nc-4.0
base_model: facebook/mms-1b-all
tags:
- automatic-speech-recognition
- bigcgen
- mms
- generated_from_trainer
metrics:
- wer
model-index:
- name: mms-1b-bigcgen-male-5hrs-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-bigcgen-male-5hrs-model
This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the BIGCGEN - BEM dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4408
- Wer: 0.4520
## 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
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- 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 |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 12.4451 | 0.3106 | 100 | 1.2035 | 0.8329 |
| 1.6342 | 0.6211 | 200 | 0.6175 | 0.5759 |
| 1.5403 | 0.9317 | 300 | 0.5695 | 0.5535 |
| 1.3778 | 1.2422 | 400 | 0.5524 | 0.5359 |
| 1.4572 | 1.5528 | 500 | 0.5302 | 0.5172 |
| 1.4042 | 1.8634 | 600 | 0.5179 | 0.5266 |
| 1.4053 | 2.1739 | 700 | 0.5029 | 0.5143 |
| 1.2782 | 2.4845 | 800 | 0.4701 | 0.4864 |
| 1.2541 | 2.7950 | 900 | 0.4585 | 0.4867 |
| 1.1672 | 3.1056 | 1000 | 0.4728 | 0.4862 |
| 1.1205 | 3.4161 | 1100 | 0.4558 | 0.4794 |
| 1.1699 | 3.7267 | 1200 | 0.4520 | 0.4811 |
| 1.2418 | 4.0373 | 1300 | 0.4495 | 0.4751 |
| 1.071 | 4.3478 | 1400 | 0.4487 | 0.4737 |
| 1.078 | 4.6584 | 1500 | 0.4446 | 0.4761 |
| 1.2474 | 4.9689 | 1600 | 0.4437 | 0.4626 |
| 1.1127 | 5.2795 | 1700 | 0.4380 | 0.4657 |
| 1.1761 | 5.5901 | 1800 | 0.4480 | 0.4674 |
| 1.0997 | 5.9006 | 1900 | 0.4470 | 0.4653 |
| 1.1203 | 6.2112 | 2000 | 0.4421 | 0.4614 |
| 1.0749 | 6.5217 | 2100 | 0.4344 | 0.4506 |
| 1.1156 | 6.8323 | 2200 | 0.4354 | 0.4511 |
| 1.0404 | 7.1429 | 2300 | 0.4364 | 0.4535 |
| 1.1081 | 7.4534 | 2400 | 0.4377 | 0.4516 |
| 1.0535 | 7.7640 | 2500 | 0.4407 | 0.4520 |
### Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
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