---
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-baseline-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-baseline-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: 0.5089
- Wer: 0.4580

## 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    |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 12.3367       | 0.3058  | 100  | 1.3241          | 0.8893 |
| 1.8764        | 0.6116  | 200  | 0.6894          | 0.5815 |
| 1.6712        | 0.9174  | 300  | 0.6390          | 0.5514 |
| 1.5044        | 1.2232  | 400  | 0.6301          | 0.5351 |
| 1.6648        | 1.5291  | 500  | 0.6076          | 0.5283 |
| 1.6411        | 1.8349  | 600  | 0.6073          | 0.5283 |
| 1.4016        | 2.1407  | 700  | 0.5994          | 0.5124 |
| 1.5703        | 2.4465  | 800  | 0.5997          | 0.5162 |
| 1.4165        | 2.7523  | 900  | 0.5850          | 0.5084 |
| 1.4703        | 3.0581  | 1000 | 0.5912          | 0.5127 |
| 1.48          | 3.3639  | 1100 | 0.5707          | 0.4999 |
| 1.4769        | 3.6697  | 1200 | 0.5675          | 0.4949 |
| 1.312         | 3.9755  | 1300 | 0.5856          | 0.4980 |
| 1.3821        | 4.2813  | 1400 | 0.5642          | 0.4992 |
| 1.457         | 4.5872  | 1500 | 0.5588          | 0.5053 |
| 1.3606        | 4.8930  | 1600 | 0.5637          | 0.4866 |
| 1.3986        | 5.1988  | 1700 | 0.5511          | 0.4866 |
| 1.421         | 5.5046  | 1800 | 0.5846          | 0.5346 |
| 1.3004        | 5.8104  | 1900 | 0.5440          | 0.4736 |
| 1.3319        | 6.1162  | 2000 | 0.5318          | 0.4786 |
| 1.2665        | 6.4220  | 2100 | 0.5488          | 0.5065 |
| 1.3703        | 6.7278  | 2200 | 0.5304          | 0.4878 |
| 1.1954        | 7.0336  | 2300 | 0.5298          | 0.4807 |
| 1.2973        | 7.3394  | 2400 | 0.5258          | 0.4706 |
| 1.2086        | 7.6453  | 2500 | 0.5231          | 0.4807 |
| 1.2796        | 7.9511  | 2600 | 0.5404          | 0.4739 |
| 1.1428        | 8.2569  | 2700 | 0.5328          | 0.4831 |
| 1.3118        | 8.5627  | 2800 | 0.5198          | 0.4769 |
| 1.2569        | 8.8685  | 2900 | 0.5306          | 0.4847 |
| 1.1718        | 9.1743  | 3000 | 0.5160          | 0.4649 |
| 1.1354        | 9.4801  | 3100 | 0.5265          | 0.4777 |
| 1.2795        | 9.7859  | 3200 | 0.5090          | 0.4590 |
| 1.1793        | 10.0917 | 3300 | 0.5265          | 0.4684 |
| 1.1647        | 10.3976 | 3400 | 0.5385          | 0.4762 |
| 1.1978        | 10.7034 | 3500 | 0.5132          | 0.4715 |
| 1.1802        | 11.0092 | 3600 | 0.5130          | 0.4597 |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0