metadata

language:
  - hi
license: apache-2.0
base_model: openai/whisper-base
tags:
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_11_0
metrics:
  - wer
model-index:
  - name: Whisper Base Fa - Mohammad Naseri
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Common Voice 11.0
          type: mozilla-foundation/common_voice_11_0
          config: fa
          split: test[:5%]
          args: 'config: fa, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 89.13105009906594

Whisper Base Fa - Mohammad Naseri

This model is a fine-tuned version of openai/whisper-base on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:

Loss: 1.3496
Wer: 89.1311

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: 16
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 10
training_steps: 100
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
No log	0.2353	20	1.6727	96.9148
1.6442	0.4706	40	1.4761	95.6128
1.1055	0.7059	60	1.3970	93.4900
0.9619	0.9412	80	1.3604	89.7538
0.8024	1.1765	100	1.3496	89.1311

Framework versions

Transformers 4.41.2
Pytorch 2.3.0+cu121
Datasets 2.20.0
Tokenizers 0.19.1