---
library_name: transformers
language:
- khm
license: cc-by-nc-4.0
base_model: facebook/mms-1b-fl102
tags:
- generated_from_trainer
datasets:
- seanghay/khmer-mpwt-speech
metrics:
- wer
model-index:
- name: mms-1b-finetuned-khm
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: seanghay/khmer-mpwt-speech
      type: seanghay/khmer-mpwt-speech
    metrics:
    - type: wer
      value: 0.627763041556145
      name: Wer
---

<!-- 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-finetuned-khm

This model is a fine-tuned version of [facebook/mms-1b-fl102](https://huggingface.co/facebook/mms-1b-fl102) on the seanghay/khmer-mpwt-speech dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5778
- Wer: 0.6278

## 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: 0.001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- 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: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 4.8181        | 0.5587 | 100  | 1.0119          | 0.9584 |
| 1.1491        | 1.1173 | 200  | 0.7723          | 0.7366 |
| 0.9737        | 1.6760 | 300  | 0.6707          | 0.7366 |
| 0.8471        | 2.2346 | 400  | 0.6370          | 0.7019 |
| 0.8114        | 2.7933 | 500  | 0.5789          | 0.6863 |
| 0.6951        | 3.3520 | 600  | 0.5461          | 0.6464 |
| 0.6791        | 3.9106 | 700  | 0.5406          | 0.6672 |


### Framework versions

- Transformers 4.57.0.dev0
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1