mim-asr-interviews-full-small-no-augmented – AI Model by joagonzalez | AlphaNeural AI

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mim-asr-interviews-full-small-no-augmented

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mim-asr-interviews-full-small-no-augmented

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

Loss: 0.8421
Wer: 75.7006

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: 32
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 1000
training_steps: 10000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0003	52.63	1000	0.6102	55.2783
0.0001	105.26	2000	0.6581	76.8522
0.0	157.89	3000	0.6936	62.1113
0.0	210.53	4000	0.7215	64.2994
0.0	263.16	5000	0.7532	65.4127
0.0	315.79	6000	0.7775	65.1440
0.0	368.42	7000	0.8028	65.0288
0.0	421.05	8000	0.8207	69.8656
0.0	473.68	9000	0.8364	70.2495
0.0	526.32	10000	0.8421	75.7006

Framework versions

Transformers 4.28.1
Pytorch 2.0.0+cu117
Datasets 2.11.0
Tokenizers 0.13.3