wav2vec2-xls-r-300m-ab-CV8

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: 0.2105
• Wer: 0.5474

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: 0.0001
• 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: 300
• num_epochs: 15
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
4.7729	0.63	500	3.0624	1.0021
2.7348	1.26	1000	1.0460	0.9815
1.2756	1.9	1500	0.4618	0.8309
1.0419	2.53	2000	0.3725	0.7449
0.9491	3.16	2500	0.3368	0.7345
0.9006	3.79	3000	0.3014	0.6936
0.8519	4.42	3500	0.2852	0.6767
0.8243	5.06	4000	0.2701	0.6504
0.7902	5.69	4500	0.2641	0.6221
0.7767	6.32	5000	0.2549	0.6192
0.7516	6.95	5500	0.2515	0.6179
0.737	7.59	6000	0.2408	0.5963
0.7217	8.22	6500	0.2429	0.6261
0.7101	8.85	7000	0.2366	0.5687
0.6922	9.48	7500	0.2277	0.5680
0.6866	10.11	8000	0.2242	0.5847
0.6703	10.75	8500	0.2222	0.5803
0.6649	11.38	9000	0.2247	0.5765
0.6513	12.01	9500	0.2182	0.5644
0.6369	12.64	10000	0.2128	0.5508
0.6425	13.27	10500	0.2132	0.5514
0.6399	13.91	11000	0.2116	0.5495
0.6208	14.54	11500	0.2105	0.5474

Framework versions

• Transformers 4.11.3
• Pytorch 1.10.0+cu111
• Datasets 1.18.1
• Tokenizers 0.10.3