mms_kik – AI Model by adityaydavalli | AlphaNeural AI

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adityaydavalli/
mms_kik

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automatic-speech-recognition

generated_from_trainer

facebook/mms-1b-all

endpoints_compatible

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mms_kik

This model is a fine-tuned version of facebook/mms-1b-all on the None dataset. It achieves the following results on the evaluation set:

Loss: inf
Wer: 0.1756

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: 0.001
train_batch_size: 4
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 100
num_epochs: 4
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
4.4384	0.1576	100	inf	0.4287
0.5264	0.3152	200	inf	0.3938
0.4716	0.4728	300	inf	0.3655
0.4084	0.6304	400	inf	0.3319
0.3953	0.7880	500	inf	0.3340
0.3605	0.9456	600	inf	0.3109
0.3601	1.1032	700	inf	0.2919
0.3368	1.2608	800	inf	0.2746
0.3102	1.4184	900	inf	0.2691
0.3209	1.5760	1000	inf	0.2602
0.2975	1.7336	1100	inf	0.2488
0.2741	1.8913	1200	inf	0.2356
0.271	2.0489	1300	inf	0.2297
0.2494	2.2065	1400	inf	0.2233
0.254	2.3641	1500	inf	0.2110
0.2484	2.5217	1600	inf	0.2117
0.2416	2.6793	1700	inf	0.2020
0.2366	2.8369	1800	inf	0.1985
0.2313	2.9945	1900	inf	0.1959
0.2228	3.1521	2000	inf	0.1897
0.2138	3.3097	2100	inf	0.1868
0.2116	3.4673	2200	inf	0.1822
0.223	3.6249	2300	inf	0.1788
0.2144	3.7825	2400	inf	0.1774
0.2131	3.9401	2500	inf	0.1756

Framework versions

Transformers 4.44.2
Pytorch 2.4.1+cu121
Datasets 3.0.0
Tokenizers 0.19.1