bkc_model1
This model is a fine-tuned version of openai/whisper-large on the data_z dataset. It achieves the following results on the evaluation set:
- eval_loss: 0.0370
- eval_cer: 1.3013
- eval_runtime: 2141.2652
- eval_samples_per_second: 1.04
- eval_steps_per_second: 0.13
- epoch: 3.5935
- step: 4000
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: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- 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: 500
- training_steps: 4000
- mixed_precision_training: Native AMP
Framework versions
- Transformers 4.46.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 3.0.0
- Tokenizers 0.20.0
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Base model
openai/whisper-large