wav2vec2-1b-E50_freq – AI Model by Gummybear05 | AlphaNeural AI

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Gummybear05/
wav2vec2-1b-E50_freq

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automatic-speech-recognition

generated_from_trainer

facebook/wav2vec2-xls-r-1b

endpoints_compatible

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wav2vec2-1b-E50_freq

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: 0.4231
Cer: 11.7951

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
9.4581	0.2580	200	3.9157	68.4387
2.071	0.5160	400	1.6011	37.3766
1.307	0.7741	600	1.1918	28.6889
1.1363	1.0321	800	1.0170	23.9192
0.8977	1.2901	1000	0.8161	20.3771
0.8219	1.5481	1200	0.7277	18.9908
0.7857	1.8062	1400	0.7119	19.1494
0.6967	2.0642	1600	0.6717	17.8748
0.5744	2.3222	1800	0.7313	19.1259
0.5676	2.5802	2000	0.6092	16.3593
0.5362	2.8383	2200	0.5840	16.5120
0.4879	3.0963	2400	0.5039	13.8745
0.4144	3.3543	2600	0.5449	14.6558
0.3875	3.6123	2800	0.4790	13.3400
0.3723	3.8703	3000	0.4497	12.3238
0.3326	4.1284	3200	0.4624	12.3825
0.2905	4.3864	3400	0.4345	12.2004
0.2745	4.6444	3600	0.4479	12.2768
0.2668	4.9024	3800	0.4231	11.7951

Framework versions

Transformers 4.45.2
Pytorch 2.3.1.post100
Datasets 2.19.1
Tokenizers 0.20.1