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whisper_film_chinese

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

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The following hyperparameters were used during training:

learning_rate: 3e-05
train_batch_size: 4
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 32
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: linear
lr_scheduler_warmup_steps: 500
num_epochs: 10
mixed_precision_training: Native AMP

Training Loss	Epoch	Step	Validation Loss	Cer
0.1133	1.0	342	0.1725	14.9216
0.0905	2.0	684	0.1929	15.9707
0.0458	3.0	1026	0.2001	15.8537
0.0192	4.0	1368	0.2084	15.9958

Safetensors

Model size

0.8B params

Tensor type

F32

Base model

Finetuned

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this model