metadata

license: apache-2.0
base_model: openai/whisper-large-v3
tags:
  - generated_from_trainer
datasets:
  - common_voice_13_0
metrics:
  - wer
model-index:
  - name: openai/whisper-large-v3
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: common_voice_13_0
          type: common_voice_13_0
          config: eu
          split: test
          args: eu
        metrics:
          - name: Wer
            type: wer
            value: 10.620114220908098

openai/whisper-large-v3

This model is a fine-tuned version of openai/whisper-large-v3 on the common_voice_13_0 dataset. It achieves the following results on the evaluation set:

Loss: 0.3803
Wer: 10.6201

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: 32
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
training_steps: 20000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0326	4.85	1000	0.2300	13.3278
0.004	9.71	2000	0.2723	12.2038
0.0058	14.56	3000	0.2771	12.4246
0.003	19.42	4000	0.2838	12.2119
0.003	24.27	5000	0.2740	11.7704
0.0014	29.13	6000	0.2936	11.5436
0.0015	33.98	7000	0.2911	11.5193
0.0012	38.83	8000	0.2939	11.3674
0.0009	43.69	9000	0.3039	11.4140
0.0002	48.54	10000	0.3063	10.9624
0.0009	53.4	11000	0.3014	11.3350
0.0011	58.25	12000	0.3052	11.0474
0.0001	63.11	13000	0.3204	10.8692
0.0	67.96	14000	0.3413	10.7092
0.0	72.82	15000	0.3524	10.6647
0.0	77.67	16000	0.3607	10.6566
0.0	82.52	17000	0.3675	10.6120
0.0	87.38	18000	0.3737	10.6140
0.0	92.23	19000	0.3782	10.6181
0.0	97.09	20000	0.3803	10.6201

Framework versions

Transformers 4.37.2
Pytorch 2.2.0+cu121
Datasets 2.16.1
Tokenizers 0.15.1