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Swahili Distill Smoke 20260709 152928

This model is a fine-tuned version of openai/whisper-tiny on the None dataset. It achieves the following results on the evaluation set: Loss: 2.2642 Wer: 92.2175 Cer: 35.3085 Avg Pred Words: 32.51 Avg Ref Words: 33.28

KindText modelBase modelopenai/whisper-tinyVersionmodel

Model source

Kind
Text model
File size
144 MB
Base model
openai/whisper-tiny
Version
vmodel
Updated
Sep 22, 2026
Downloads
3
Source
Hugging Face

Source description

swahili-distill_smoke-20260709-152928

This model is a fine-tuned version of openai/whisper-tiny on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 2.2642
  • Wer: 92.2175
  • Cer: 35.3085
  • Avg Pred Words: 32.51
  • Avg Ref Words: 33.28

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: 1e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 4
  • 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: 500
  • training_steps: 100
  • mixed_precision_training: Native AMP

Training results

Training LossEpochStepValidation LossWerCerAvg Pred WordsAvg Ref Words
2.9971.5714253.4215102.313738.337334.2133.28
2.74643.1270503.0001105.619039.496036.6933.28
2.40574.6984752.6360101.923143.631734.8533.28
2.06976.25401002.264292.217535.308532.5133.28

Framework versions

  • Transformers 4.57.6
  • Pytorch 2.10.0+cu128
  • Datasets 3.6.0
  • Tokenizers 0.22.2

Sources

1 source
Hugging FacePrimaryVersion c0bf6678723eebbb07fcdad2040d17d334027b16
huggingface.co/Rogendo/swahili-distill_smoke-20260709-152928/tree/c0bf6678723eebbb07fcdad2040d17d334027b16

Verified Sep 22

Model artifacts

1 artifact

model.safetensors

safetensors · 144 MB · SHA-256 4c5a42a7d3c6…2fc0 · Hugging Face

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Source excerpts

2 excerpts

--- library_name: transformers license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_trainer metrics: - wer model-index: - name: swahili-distill_smoke-20260709-152928 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. --> # swahili-distill_smoke-20260709-152928 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the None dataset. It achieves the following results on the evaluation set: - Loss: 2.2642 - Wer: 92.2175 - Cer: 35.3085 - Avg Pred Words: 32.51 - Avg Ref Words: 33.28 ## 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: 1e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 4 - 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: 500 - training_steps: 100 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | Cer | Avg Pred Words | Avg Ref Words | |:-------------:|:------:|:----:|:---------------:|:--------:|:-------:|:--------------:|:-------------:| | 2.997 | 1.5714 | 25 | 3.4215 | 102.3137 | 38.3373 | 34.21 | 33.28 | | 2.7464 | 3.1270 | 50 | 3.0001 | 105.6190 | 39.4960 | 36.69 | 33.28 | | 2.4057 | 4.6984 | 75 | 2.6360 | 101.9231 | 43.6317 | 34.85 | 33.28 | | 2.0697 | 6.2540 | 100 | 2.2642 | 92.2175 | 35.3085 | 32.51 | 33.28 | ### Framework versions - Transformers 4.57.6 - Pytorch 2.10.0+cu128 - Datasets 3.6.0 - Tokenizers 0.22.2

Source context: 3 downloads · 0 likes · Pipeline automatic-speech-recognition · Library transformers · Repo Rogendo/swahili-distill_smoke-20260709-152928