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

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: 0.7539
• Wer: 0.6135

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
11.1466	1.0	118	4.3444	1.0
3.4188	2.0	236	3.2496	1.0
2.8617	3.0	354	1.6165	1.0003
0.958	4.0	472	0.7984	0.8720
0.5929	5.0	590	0.6733	0.7831
0.4628	6.0	708	0.6536	0.7621
0.3834	7.0	826	0.6037	0.7155
0.3242	8.0	944	0.6376	0.7184
0.2736	9.0	1062	0.6214	0.7070
0.2433	10.0	1180	0.6158	0.6944
0.2217	11.0	1298	0.6548	0.6830
0.1992	12.0	1416	0.6331	0.6775
0.1804	13.0	1534	0.6644	0.6874
0.1639	14.0	1652	0.6629	0.6649
0.143	15.0	1770	0.6927	0.6836
0.1394	16.0	1888	0.6933	0.6888
0.1296	17.0	2006	0.7039	0.6860
0.1212	18.0	2124	0.7042	0.6628
0.1121	19.0	2242	0.7132	0.6475
0.1069	20.0	2360	0.7423	0.6438
0.1063	21.0	2478	0.7171	0.6484
0.1025	22.0	2596	0.7396	0.6451
0.0946	23.0	2714	0.7400	0.6432
0.0902	24.0	2832	0.7385	0.6286
0.0828	25.0	2950	0.7368	0.6286
0.079	26.0	3068	0.7471	0.6306
0.0747	27.0	3186	0.7524	0.6201
0.0661	28.0	3304	0.7576	0.6201
0.0659	29.0	3422	0.7579	0.6130
0.0661	30.0	3540	0.7539	0.6135

Framework versions

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