metadata

language:
  - zh
license: apache-2.0
base_model: openai/whisper-large-v2
tags:
  - generated_from_trainer
datasets:
  - LeoKuo49/Amitabha_all
model-index:
  - name: Whisper-finetune_all
    results: []

Whisper-finetune_all

This model is a fine-tuned version of openai/whisper-large-v2 on the Amitabha_all dataset. It achieves the following results on the evaluation set:

Loss: 0.0003
Cer: 0.2260

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: 500
training_steps: 4000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Cer
0.1067	2.5253	1000	0.0800	11.4694
0.0133	5.0505	2000	0.0102	3.3448
0.0017	7.5758	3000	0.0014	0.3232
0.0002	10.1010	4000	0.0003	0.2260

Framework versions

Transformers 4.41.2
Pytorch 2.3.0+cu121
Datasets 2.20.0
Tokenizers 0.19.1