wav2vec2-1b-E10_freq_pause_speed – AI Model by Gummybear05 | AlphaNeural AI

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Gummybear05/
wav2vec2-1b-E10_freq_pause_speed

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automatic-speech-recognition

generated_from_trainer

facebook/wav2vec2-xls-r-1b

endpoints_compatible

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wav2vec2-1b-E10_freq_pause_speed

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: 1.0591
Cer: 29.8990

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
14.1255	0.2580	200	4.9067	98.6372
4.7267	0.5160	400	4.8958	92.8806
4.5507	0.7741	600	4.7162	92.6281
4.3966	1.0321	800	4.4020	92.5928
3.6541	1.2901	1000	2.9100	59.9918
1.9909	1.5481	1200	2.1571	52.5200
1.4189	1.8062	1400	1.6267	39.1506
1.1011	2.0642	1600	1.6680	44.1259
0.8993	2.3222	1800	1.6389	43.5562
0.8212	2.5802	2000	1.6651	42.0054
0.7402	2.8383	2200	1.3370	37.4413
0.671	3.0963	2400	1.2070	34.4690
0.551	3.3543	2600	1.2536	35.7554
0.4977	3.6123	2800	1.1724	33.1062
0.4612	3.8703	3000	1.0322	29.5700
0.4048	4.1284	3200	1.0640	30.6156
0.3543	4.3864	3400	1.1424	30.9974
0.3354	4.6444	3600	1.0794	29.9577
0.3099	4.9024	3800	1.0591	29.8990

Framework versions

Transformers 4.45.2
Pytorch 2.3.1.post100
Datasets 2.19.1
Tokenizers 0.20.1