w2v-bert-Tamil-large – AI Model by Anujgr8 | AlphaNeural AI

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Anujgr8/
w2v-bert-Tamil-large

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automatic-speech-recognition

generated_from_trainer

facebook/w2v-bert-2.0

endpoints_compatible

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w2v-bert-Tamil-large

This model is a fine-tuned version of facebook/w2v-bert-2.0 on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.1815
Wer: 0.2176
Cer: 0.0328

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-05
train_batch_size: 2
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 8
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
training_steps: 3000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer	Cer
2.0779	0.75	300	0.4934	0.6338	0.1189
0.3653	1.5	600	0.4045	0.5424	0.0975
0.2632	2.25	900	0.3148	0.4421	0.0723
0.2084	3.0	1200	0.2297	0.3499	0.0576
0.1359	3.75	1500	0.2042	0.3060	0.0464
0.1049	4.5	1800	0.1939	0.2836	0.0446
0.0823	5.25	2100	0.1827	0.2504	0.0382
0.0561	6.0	2400	0.1731	0.2419	0.0368
0.0352	6.75	2700	0.1802	0.2275	0.0335
0.0224	7.5	3000	0.1815	0.2176	0.0328

Framework versions

Transformers 4.42.0.dev0
Pytorch 2.3.0+cu121
Datasets 2.20.0
Tokenizers 0.19.1