---
library_name: transformers
license: mit
base_model: Sunbird/asr-whisper-large-v3-salt
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: cdli-whisper-ml-eng-lug-full-a40-5e-5
  results: []
datasets:
- cdli/ugandan_luganda_nonstandard_speech_v1.0
- cdli/ugandan_english_nonstandard_speech_v1.0
---

<!-- 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. -->

# cdli-whisper-ml-eng-lug-full-a40-5e-5

This is a multilingual model and is a fine-tuned version of [Sunbird/asr-whisper-large-v3-salt](https://huggingface.co/Sunbird/asr-whisper-large-v3-salt) on the Ugandan CDLI Atypical speech datasets.
It achieves the following results on the evaluation set:
- Loss: 1.2283
- Wer: 0.4137
- Cer: 0.2271

On the test set with repetition penalty of 1.3 and no_repeat_ngram_size of 2 it obtains:
- test_cer                =     0.1268
- test_loss               =     0.8137
- test_runtime            = 0:22:24.23
- test_samples_per_second =      1.518
- test_steps_per_second   =      0.379
- test_wer                =     0.2851

# English

- Overall WER (normalized): 0.224
- Overall CER (normalized): 0.135
- Avg WER (normalized): 0.214
- Avg CER (normalized): 0.133


# Luganda

- Overall WER (normalized): 0.414
- Overall CER (normalized): 0.146
- Avg WER (normalized): 0.354
- Avg CER (normalized): 0.12

## Model description

The training was resumed from epoch 7.2255 and the Wer reported after that is a bit dirty (CER instead of WER)

## 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: 5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- 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: 150
- training_steps: 4000

### Training results

| Training Loss | Epoch   | Step | Cer    | Validation Loss | Wer    |
|:-------------:|:-------:|:----:|:------:|:---------------:|:------:|
| 0.6253        | 0.7228  | 250  | 0.2722 | 0.8156          | 0.4660 |
| 0.4188        | 1.4452  | 500  | 0.2362 | 0.8119          | 0.4247 |
| 0.2709        | 2.1677  | 750  | 0.2352 | 0.8229          | 0.4206 |
| 0.2571        | 2.8905  | 1000 | 0.2261 | 0.8141          | 0.4153 |
| 0.1581        | 3.6129  | 1250 | 0.2292 | 0.9097          | 0.4167 |
| 0.083         | 4.3354  | 1500 | 0.2271 | 0.9749          | 0.4177 |
| 0.0593        | 5.0578  | 1750 | 0.2266 | 1.0613          | 0.4107 |
| 0.0518        | 5.7806  | 2000 | 0.2235 | 1.0547          | 0.4108 |
| 0.0382        | 6.5031  | 2250 | 0.2249 | 1.1098          | 0.4095 |
| 0.0356        | 7.2255  | 2500 | 0.2238 | 1.1149          | 0.4087 |
| 0.0408        | 7.9483  | 2750 | 1.1168 | 0.4139          | 0.2261 |
| 0.0368        | 8.6737  | 3000 | 1.1499 | 0.4172          | 0.2279 |
| 0.0271        | 9.3961  | 3250 | 1.2052 | 0.4132          | 0.2271 |
| 0.0237        | 10.1185 | 3500 | 1.2107 | 0.4114          | 0.2263 |
| 0.0212        | 10.8413 | 3750 | 1.2275 | 0.4111          | 0.2250 |
| 0.0221        | 11.5638 | 4000 | 1.2283 | 0.4137          | 0.2271 |


### Framework versions

- Transformers 4.52.0
- Pytorch 2.7.1+cu118
- Datasets 3.6.0
- Tokenizers 0.21.4