|
--- |
|
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-female-15hrs-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-female-15hrs-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: inf |
|
- Wer: 0.5205 |
|
|
|
## 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 |
|
- training_steps: 2500 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|:-------------:|:------:|:----:|:---------------:|:------:| |
|
| 14.809 | 0.1003 | 100 | inf | 1.0120 | |
|
| 6.0699 | 0.2005 | 200 | inf | 0.9993 | |
|
| 5.3221 | 0.3008 | 300 | inf | 1.0347 | |
|
| 4.0785 | 0.4010 | 400 | inf | 0.7821 | |
|
| 2.0743 | 0.5013 | 500 | inf | 0.6082 | |
|
| 1.7578 | 0.6015 | 600 | inf | 0.5732 | |
|
| 1.8081 | 0.7018 | 700 | inf | 0.5659 | |
|
| 1.7107 | 0.8020 | 800 | inf | 0.5478 | |
|
| 1.7206 | 0.9023 | 900 | inf | 0.5489 | |
|
| 1.6957 | 1.0020 | 1000 | inf | 0.5446 | |
|
| 1.587 | 1.1023 | 1100 | inf | 0.5380 | |
|
| 1.5794 | 1.2025 | 1200 | inf | 0.5355 | |
|
| 1.4728 | 1.3028 | 1300 | inf | 0.5251 | |
|
| 1.5137 | 1.4030 | 1400 | inf | 0.5380 | |
|
| 1.5073 | 1.5033 | 1500 | inf | 0.5294 | |
|
| 1.3676 | 1.6035 | 1600 | inf | 0.5271 | |
|
| 1.5592 | 1.7038 | 1700 | inf | 0.5240 | |
|
| 1.5091 | 1.8040 | 1800 | inf | 0.5682 | |
|
| 1.5439 | 1.9043 | 1900 | inf | 0.5208 | |
|
| 1.4025 | 2.0040 | 2000 | inf | 0.5276 | |
|
| 1.465 | 2.1043 | 2100 | inf | 0.5269 | |
|
| 1.4096 | 2.2045 | 2200 | inf | 0.5346 | |
|
| 1.428 | 2.3048 | 2300 | inf | 0.5212 | |
|
| 1.3829 | 2.4050 | 2400 | inf | 0.5217 | |
|
| 1.3048 | 2.5053 | 2500 | inf | 0.5205 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.47.1 |
|
- Pytorch 2.5.1+cu124 |
|
- Datasets 3.2.0 |
|
- Tokenizers 0.21.0 |
|
|
