metadata

library_name: transformers
license: apache-2.0
base_model: openai/whisper-tiny.en
tags:
  - generated_from_trainer
datasets:
  - lalipa/jv_id_asr_split
metrics:
  - wer
model-index:
  - name: hyperparameter
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: lalipa/jv_id_asr_split jv_id_asr_source
          type: lalipa/jv_id_asr_split
          config: jv_id_asr_source
          split: validation
          args: jv_id_asr_source
        metrics:
          - name: Wer
            type: wer
            value: 0.6883827458964245

hyperparameter

This model is a fine-tuned version of openai/whisper-tiny.en on the lalipa/jv_id_asr_split jv_id_asr_source dataset. It achieves the following results on the evaluation set:

Loss: 1.4506
Wer: 0.6884
Cer: 0.2050

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: 16
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 32
optimizer: Use adamw_torch 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: 100
training_steps: 300

Training results

Training Loss	Epoch	Step	Validation Loss	Wer	Cer
3.9694	0.1020	30	3.7782	1.8748	1.0887
3.3735	0.2041	60	2.9598	1.0019	0.4254
2.5449	0.3061	90	2.1989	0.8820	0.3221
1.9987	0.4082	120	1.8648	0.8004	0.2606
1.7671	0.5102	150	1.6909	0.7619	0.2312
1.6285	0.6122	180	1.5863	0.7336	0.2245
1.5475	0.7143	210	1.5251	0.7216	0.2213
1.4793	0.8163	240	1.4807	0.6942	0.2035
1.5013	0.9184	270	1.4582	0.6904	0.2057
1.4438	1.0204	300	1.4506	0.6884	0.2050

Framework versions

Transformers 4.46.0.dev0
Pytorch 2.4.1
Datasets 3.0.1
Tokenizers 0.20.0