wav2vec2-large-xls-r-300m-tamil-colab

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common_voice dataset. It achieves the following results on the evaluation set:

• Loss: 0.8072
• Wer: 0.6531

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: 16
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 32
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 500
• num_epochs: 30
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
11.0967	1.0	118	4.6437	1.0
3.4973	2.0	236	3.2588	1.0
3.1305	3.0	354	2.6566	1.0
1.2931	4.0	472	0.9156	0.9944
0.6851	5.0	590	0.7474	0.8598
0.525	6.0	708	0.6649	0.7995
0.4325	7.0	826	0.6740	0.7752
0.3766	8.0	944	0.6220	0.7628
0.3256	9.0	1062	0.6316	0.7322
0.2802	10.0	1180	0.6442	0.7305
0.2575	11.0	1298	0.6885	0.7280
0.2248	12.0	1416	0.6702	0.7197
0.2089	13.0	1534	0.6781	0.7173
0.1893	14.0	1652	0.6981	0.7049
0.1652	15.0	1770	0.7154	0.7436
0.1643	16.0	1888	0.6798	0.7023
0.1472	17.0	2006	0.7381	0.6947
0.1372	18.0	2124	0.7240	0.7065
0.1318	19.0	2242	0.7305	0.6714
0.1211	20.0	2360	0.7288	0.6597
0.1178	21.0	2478	0.7417	0.6699
0.1118	22.0	2596	0.7476	0.6753
0.1016	23.0	2714	0.7973	0.6647
0.0998	24.0	2832	0.8027	0.6633
0.0917	25.0	2950	0.8045	0.6680
0.0907	26.0	3068	0.7884	0.6565
0.0835	27.0	3186	0.8009	0.6622
0.0749	28.0	3304	0.8123	0.6536
0.0755	29.0	3422	0.8006	0.6555
0.074	30.0	3540	0.8072	0.6531

Framework versions

• Transformers 4.11.3
• Pytorch 1.10.0+cu111
• Datasets 1.13.3
• Tokenizers 0.10.3