whisper-tinyfinacial – AI Model by controngo | AlphaNeural AI

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controngo/
whisper-tinyfinacial

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automatic-speech-recognition

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openai/whisper-tiny

endpoints_compatible

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whisper-tinyfinacial

This model is a fine-tuned version of openai/whisper-tiny on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.5217
Wer: 55.6180

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: 1.35e-05
train_batch_size: 8
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: 100
training_steps: 600

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
No log	0.4	50	0.9091	64.0449
No log	0.8	100	0.6941	52.2472
No log	1.2	150	0.5615	51.6854
No log	1.6	200	0.5219	47.1910
No log	2.0	250	0.4938	47.7528
No log	2.4	300	0.4970	50.0
No log	2.8	350	0.4999	58.4270
No log	3.2	400	0.5076	46.0674
No log	3.6	450	0.5157	52.2472
0.3104	4.0	500	0.5277	56.1798
0.3104	4.4	550	0.5257	57.3034
0.3104	4.8	600	0.5217	55.6180

Framework versions

Transformers 4.41.2
Pytorch 2.3.0+cu121
Datasets 2.20.0
Tokenizers 0.19.1