FT-English-10ha – AI Model by Pageee | AlphaNeural AI

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Pageee/
FT-English-10ha

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automatic-speech-recognition

generated_from_trainer

librispeech_asr

openai/whisper-small

endpoints_compatible

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Whisper-Small En-10h

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

Loss: 0.1307
Wer: 3.9809

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: 5e-07
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 300
training_steps: 1000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.525	0.5556	100	0.7431	3.4571
0.382	1.1111	200	0.5645	3.4836
0.1704	1.6667	300	0.2111	4.0237
0.0953	2.2222	400	0.1527	4.1114
0.0904	2.7778	500	0.1404	4.0400
0.0784	3.3333	600	0.1355	4.0482
0.0793	3.8889	700	0.1331	3.9768
0.0776	4.4444	800	0.1318	3.9646
0.0629	5.0	900	0.1310	3.9830
0.0746	5.5556	1000	0.1307	3.9809

Framework versions

Transformers 4.41.0.dev0
Pytorch 2.3.0+cu121
Datasets 2.19.1
Tokenizers 0.19.1