| | --- |
| | library_name: transformers |
| | license: cc-by-nc-4.0 |
| | base_model: Serialtechlab/mms-1b-dhivehi-finetuned |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - wer |
| | model-index: |
| | - name: mms-1b-dhivehi-v2 |
| | 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-dhivehi-v2 |
| |
|
| | This model is a fine-tuned version of [Serialtechlab/mms-1b-dhivehi-finetuned](https://huggingface.co/Serialtechlab/mms-1b-dhivehi-finetuned) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.3861 |
| | - Wer: 0.5432 |
| |
|
| | ## 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: 3e-05 |
| | - train_batch_size: 8 |
| | - eval_batch_size: 8 |
| | - seed: 42 |
| | - gradient_accumulation_steps: 2 |
| | - total_train_batch_size: 16 |
| | - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 3 |
| | - mixed_precision_training: Native AMP |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Wer | |
| | |:-------------:|:------:|:----:|:---------------:|:------:| |
| | | 0.6271 | 0.8292 | 500 | 0.3889 | 0.5458 | |
| | | 0.5948 | 1.6584 | 1000 | 0.3871 | 0.5438 | |
| | | 0.5946 | 2.4876 | 1500 | 0.3861 | 0.5432 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.57.3 |
| | - Pytorch 2.9.0+cu126 |
| | - Datasets 4.0.0 |
| | - Tokenizers 0.22.1 |
| | |
