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Whisper Large v3 Turbo Persian Audiodata2

This model is a fine-tuned version of openai/whisper-large-v3-turbo on an unknown dataset. It achieves the following results on the evaluation set: Loss: 1.1979 Wer: 42.4096

TypeLoRAModèle de baseopenai/whisper-large-v3-turboVersionadapter_model

Source du modèle

Type
LoRA
Taille du fichier
50,0 MB
Modèle de base
openai/whisper-large-v3-turbo
Version
vadapter_model
Mis à jour
14 sept. 2026
Téléchargements
10
Source
Hugging Face

Description de la source

whisper-large-v3-turbo-persian-audiodata2

This model is a fine-tuned version of openai/whisper-large-v3-turbo on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 1.1979
  • Wer: 42.4096

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: 4
  • 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: cosine
  • lr_scheduler_warmup_steps: 50
  • num_epochs: 100

Training results

Training LossEpochStepValidation LossWer
2.04201.051.228044.8996
1.99902.0101.184045.0602
1.89693.0151.120043.2932
1.79664.0201.041943.7751
1.58805.0250.971642.4096
1.41816.0300.919138.8755
1.28447.0350.870536.0643
1.08768.0400.837138.0723
0.94739.0450.843741.0442
0.923210.0500.815938.7149
0.923226.0520.809138.7952
0.923227.0540.804339.3574
0.592828.0560.802940.1606
0.592829.0580.798738.3133
0.471430.0600.803837.0281
0.471431.0620.809836.3052
0.471432.0640.808336.7871
0.455533.0660.813638.7149
0.455534.0680.821739.4378
0.432835.0700.831038.6345
0.432836.0720.837137.5904
0.432837.0740.848237.9116
0.406138.0760.851037.9116
0.406139.0780.854540.0803
0.256140.0800.857740.4819
0.256141.0820.864240.8032
0.256142.0840.878239.5181
0.322443.0860.892840.9639
0.322444.0880.900241.7671
0.298245.0900.902040.6426
0.298246.0920.906142.1687
0.298247.0940.926241.4458
0.262548.0960.940141.6867
0.262549.0980.942140.1606
0.226250.01000.956443.8554
0.226251.01020.963645.7028
0.345121.01050.979540.8835
0.285422.01101.001146.1847
0.287623.01150.965042.2490
0.273324.01200.940539.9197
0.269025.01251.001741.6867
0.246126.01300.971239.0361
0.233827.01350.992739.9197
0.252028.01401.005441.8474
0.218429.01450.988140.0
0.206430.01500.991540.5622
0.195931.01551.021840.6426
0.186732.01601.050440.4819
0.177433.01651.011339.7590
0.182134.01701.035739.9197
0.156135.01751.031040.4819
0.142936.01801.066842.4096
0.130737.01851.038341.8474
0.114738.01901.079441.0442
0.110639.01951.061040.8835
0.109340.02001.093441.6867
0.098241.02051.068240.6426
0.087942.02101.083239.7590
0.085543.02151.112940.8835
0.071644.02201.106042.4096
0.079945.02251.098041.0442
0.072946.02301.116541.2048
0.069047.02351.106840.4016
0.062248.02401.106640.2410
0.060449.02451.099942.0884
0.053250.02501.107242.0884
0.050751.02551.110541.7671
0.044952.02601.112142.2490
0.040253.02651.147541.6867
0.037454.02701.163841.4458
0.036655.02751.128342.4096
0.034956.02801.147641.8474
0.033157.02851.176141.2851
0.029358.02901.168841.5261
0.031759.02951.136741.2048
0.027260.03001.156941.2048
0.026861.03051.189642.2490
0.025162.03101.166742.4900
0.024363.03151.171942.1687
0.025264.03201.188644.1767
0.024465.03251.184242.5703
0.022366.03301.177042.0080
0.021067.03351.184442.4096
0.020568.03401.182542.2490
0.020169.03451.177242.5703
0.020070.03501.182541.7671
0.020471.03551.182241.6867
0.019572.03601.188542.9719
0.019573.03651.187442.8112
0.018774.03701.184342.3293
0.018375.03751.184743.4538
0.018276.03801.190842.5703
0.017077.03851.194242.3293
0.017078.03901.190342.3293
0.017679.03951.195442.6506
0.017480.04001.191042.8112
0.017981.04051.193842.7309
0.017382.04101.197843.0522
0.016283.04151.192644.0964
0.016584.04201.194043.3735
0.017285.04251.194143.3735
0.016786.04301.194942.8916
0.016287.04351.196843.9357
0.016488.04401.196643.0522
0.016489.04451.197542.8112
0.016990.04501.199342.5703
0.016491.04551.196942.7309
0.015492.04601.197842.3293
0.015993.04651.197442.3293
0.016394.04701.199941.7671
0.016195.04751.195842.0884
0.015396.04801.197642.0884
0.016297.04851.196142.6506
0.016798.04901.198842.1687
0.015999.04951.198542.6506
0.0164100.05001.197942.4096

Framework versions

  • PEFT 0.19.1
  • Transformers 5.13.1
  • Pytorch 2.11.0+cu128
  • Datasets 4.0.0
  • Tokenizers 0.22.2

Sources

1 source
Hugging FacePrincipalVersion 9a0d262554451910a33ec8ab25b06e25d89c6c73
huggingface.co/tivanai2020/whisper-large-v3-turbo-persian-audiodata2/tree/9a0d262554451910a33ec8ab25b06e25d89c6c73

Vérifié 14 sept.

Artefacts du modèle

1 artefact

adapter_model.safetensors

safetensors · 50,0 MB · SHA-256 fc73ba7894ce…8db0 · Hugging Face

Download file

Extraits de sources

2 extraits

--- library_name: peft license: mit base_model: openai/whisper-large-v3-turbo tags: - base_model:adapter:openai/whisper-large-v3-turbo - lora - transformers metrics: - wer model-index: - name: whisper-large-v3-turbo-persian-audiodata2 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. --> # whisper-large-v3-turbo-persian-audiodata2 This model is a fine-tuned version of [openai/whisper-large-v3-turbo](https://huggingface.co/openai/whisper-large-v3-turbo) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 1.1979 - Wer: 42.4096 ## 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: 4 - 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: cosine - lr_scheduler_warmup_steps: 50 - num_epochs: 100 ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:----:|:---------------:|:-------:| | 2.0420 | 1.0 | 5 | 1.2280 | 44.8996 | | 1.9990 | 2.0 | 10 | 1.1840 | 45.0602 | | 1.8969 | 3.0 | 15 | 1.1200 | 43.2932 | | 1.7966 | 4.0 | 20 | 1.0419 | 43.7751 | | 1.5880 | 5.0 | 25 | 0.9716 | 42.4096 | | 1.4181 | 6.0 | 30 | 0.9191 | 38.8755 | | 1.2844 | 7.0 | 35 | 0.8705 | 36.0643 | | 1.0876 | 8.0 | 40 | 0.8371 | 38.0723 | | 0.9473 | 9.0 | 45 | 0.8437 | 41.0442 | | 0.9232 | 10.0 | 50 | 0.8159 | 38.7149 | | 0.9232 | 26.0 | 52 | 0.8091 | 38.7952 | | 0.9232 | 27.0 | 54 | 0.8043 | 39.3574 | | 0.5928 | 28.0 | 56 | 0.8029 | 40.1606 | | 0.5928 | 29.0 | 58 | 0.7987 | 38.3133 | | 0.4714 | 30.0 | 60 | 0.8038 | 37.0281 | | 0.4714 | 31.0 | 62 | 0.8098 | 36.3052 | | 0.4714 | 32.0 | 64 | 0.8083 | 36.7871 | | 0.4555 | 33.0 | 66 | 0.8136 | 38.7149 | | 0.4555 | 34.0 | 68 | 0.8217 | 39.4378 | | 0.4328 | 35.0 | 70 | 0.8310 | 38.6345 | | 0.4328 | 36.0 | 72 | 0.8371 | 37.5904 | | 0.4328 | 37.0 | 74 | 0.8482...

Source context: 10 downloads · 0 likes · Library peft · Repo tivanai2020/whisper-large-v3-turbo-persian-audiodata2