wav2vec2-1b-E30_speed2 – AI Model by Gummybear05 | AlphaNeural AI

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Gummybear05/
wav2vec2-1b-E30_speed2

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automatic-speech-recognition

generated_from_trainer

facebook/wav2vec2-xls-r-1b

endpoints_compatible

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wav2vec2-1b-E30_speed2

This model is a fine-tuned version of facebook/wav2vec2-xls-r-1b on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.5694
Cer: 15.0846

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: 0.0001
train_batch_size: 2
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 8
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: 50
num_epochs: 5
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Cer
14.0019	0.2580	200	4.4372	96.3816
2.5022	0.5160	400	2.0994	52.6786
1.4318	0.7741	600	1.5913	40.9657
1.1099	1.0321	800	1.2436	29.9930
0.8555	1.2901	1000	1.0155	24.9530
0.8201	1.5481	1200	0.9694	24.3715
0.7405	1.8062	1400	0.9278	24.3480
0.6497	2.0642	1600	0.9973	25.2056
0.573	2.3222	1800	0.9353	23.7723
0.5129	2.5802	2000	0.8295	21.0115
0.4662	2.8383	2200	0.7473	18.8440
0.4075	3.0963	2400	0.7551	20.4182
0.3506	3.3543	2600	0.6929	18.4387
0.3115	3.6123	2800	0.6474	17.4636
0.3061	3.8703	3000	0.6699	17.4460
0.2554	4.1284	3200	0.6221	16.2418
0.2153	4.3864	3400	0.6394	16.9937
0.1994	4.6444	3600	0.6119	15.9833
0.1915	4.9024	3800	0.5694	15.0846

Framework versions

Transformers 4.45.2
Pytorch 2.3.1.post100
Datasets 2.19.1
Tokenizers 0.20.1