---
library_name: transformers
base_model: oluwagbotty/CS_mms_eng_yor
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: CS_mms_eng_yor
  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. -->

# CS_mms_eng_yor

This model is a fine-tuned version of [oluwagbotty/CS_mms_eng_yor](https://huggingface.co/oluwagbotty/CS_mms_eng_yor) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3397
- Wer: 0.3218

## 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: 0.0005705665024630542
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 1
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 2.3476        | 0.2436 | 100  | 0.4135          | 0.3730 |
| 0.4631        | 0.4872 | 200  | 0.3958          | 0.3640 |
| 0.4441        | 0.7308 | 300  | 0.3826          | 0.3493 |
| 0.4367        | 0.9744 | 400  | 0.3784          | 0.3522 |
| 0.424         | 1.2168 | 500  | 0.3734          | 0.3468 |
| 0.4256        | 1.4604 | 600  | 0.3760          | 0.3516 |
| 0.4189        | 1.7040 | 700  | 0.3739          | 0.3474 |
| 0.4293        | 1.9476 | 800  | 0.3678          | 0.3448 |
| 0.4105        | 2.1900 | 900  | 0.3663          | 0.3466 |
| 0.3981        | 2.4336 | 1000 | 0.3736          | 0.3441 |
| 0.4161        | 2.6772 | 1100 | 0.3725          | 0.3487 |
| 0.4188        | 2.9208 | 1200 | 0.3628          | 0.3434 |
| 0.3984        | 3.1632 | 1300 | 0.3671          | 0.3426 |
| 0.4108        | 3.4068 | 1400 | 0.3674          | 0.3410 |
| 0.3905        | 3.6504 | 1500 | 0.3593          | 0.3388 |
| 0.3977        | 3.8940 | 1600 | 0.3626          | 0.3387 |
| 0.3961        | 4.1364 | 1700 | 0.3610          | 0.3322 |
| 0.3844        | 4.3800 | 1800 | 0.3644          | 0.3423 |
| 0.3938        | 4.6236 | 1900 | 0.3554          | 0.3355 |
| 0.3808        | 4.8672 | 2000 | 0.3579          | 0.3349 |
| 0.3822        | 5.1096 | 2100 | 0.3562          | 0.3330 |
| 0.3755        | 5.3532 | 2200 | 0.3556          | 0.3307 |
| 0.3789        | 5.5968 | 2300 | 0.3514          | 0.3303 |
| 0.3742        | 5.8404 | 2400 | 0.3472          | 0.3328 |
| 0.3608        | 6.0828 | 2500 | 0.3470          | 0.3276 |
| 0.3647        | 6.3264 | 2600 | 0.3468          | 0.3295 |
| 0.3719        | 6.5700 | 2700 | 0.3457          | 0.3260 |
| 0.3678        | 6.8136 | 2800 | 0.3423          | 0.3179 |
| 0.3575        | 7.0560 | 2900 | 0.3422          | 0.3201 |
| 0.3427        | 7.2996 | 3000 | 0.3516          | 0.3232 |
| 0.3661        | 7.5432 | 3100 | 0.3420          | 0.3216 |
| 0.3502        | 7.7868 | 3200 | 0.3430          | 0.3238 |
| 0.3681        | 8.0292 | 3300 | 0.3388          | 0.3201 |
| 0.3454        | 8.2728 | 3400 | 0.3397          | 0.3218 |


### Framework versions

- Transformers 4.52.0.dev0
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1