shivam/wav2vec2-xls-r-300m-hindi

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - HI dataset. It achieves the following results on the evaluation set:

• Loss: 1.4031
• Wer: 0.6827

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: 7.5e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 4
• 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: 2000
• num_epochs: 100.0
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
5.3156	3.4	500	4.5583	1.0
3.3329	6.8	1000	3.4274	1.0001
2.1275	10.2	1500	1.7221	0.8763
1.5737	13.6	2000	1.4188	0.8143
1.3835	17.01	2500	1.2251	0.7447
1.3247	20.41	3000	1.2827	0.7394
1.231	23.81	3500	1.2216	0.7074
1.1819	27.21	4000	1.2210	0.6863
1.1546	30.61	4500	1.3233	0.7308
1.0902	34.01	5000	1.3251	0.7010
1.0749	37.41	5500	1.3274	0.7235
1.0412	40.81	6000	1.2942	0.6856
1.0064	44.22	6500	1.2581	0.6732
1.0006	47.62	7000	1.2767	0.6885
0.9518	51.02	7500	1.2966	0.6925
0.9514	54.42	8000	1.2981	0.7067
0.9241	57.82	8500	1.3835	0.7124
0.9059	61.22	9000	1.3318	0.7083
0.8906	64.62	9500	1.3640	0.6962
0.8468	68.03	10000	1.4727	0.6982
0.8631	71.43	10500	1.3401	0.6809
0.8154	74.83	11000	1.4124	0.6955
0.7953	78.23	11500	1.4245	0.6950
0.818	81.63	12000	1.3944	0.6995
0.7772	85.03	12500	1.3735	0.6785
0.7857	88.43	13000	1.3696	0.6808
0.7705	91.84	13500	1.4101	0.6870
0.7537	95.24	14000	1.4178	0.6832
0.7734	98.64	14500	1.4027	0.6831

Framework versions

• Transformers 4.16.0.dev0
• Pytorch 1.10.1+cu113
• Datasets 1.18.1.dev0
• Tokenizers 0.11.0