wav2vec2-base-Tamil-large – AI Model by Anujgr8 | AlphaNeural AI

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Anujgr8/
wav2vec2-base-Tamil-large

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automatic-speech-recognition

generated_from_trainer

facebook/wav2vec2-base-960h

endpoints_compatible

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wav2vec2-base-Tamil-large

This model is a fine-tuned version of facebook/wav2vec2-base-960h on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.3015
Wer: 0.3470
Cer: 0.0610

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: 0.0003
train_batch_size: 6
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 24
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
5.2014	2.2472	300	3.2558	1.0	1.0
1.1765	4.4944	600	0.5245	0.7139	0.1482
0.4765	6.7416	900	0.4191	0.6080	0.1133
0.33	8.9888	1200	0.3494	0.4983	0.0910
0.2488	11.2360	1500	0.3163	0.4470	0.0811
0.1951	13.4831	1800	0.3326	0.4179	0.0748
0.1586	15.7303	2100	0.3135	0.3924	0.0702
0.1308	17.9775	2400	0.3070	0.3798	0.0668
0.1111	20.2247	2700	0.2999	0.3618	0.0635
0.0996	22.4719	3000	0.3015	0.3470	0.0610

Framework versions

Transformers 4.41.2
Pytorch 2.3.0+cu121
Datasets 1.18.3
Tokenizers 0.19.1