wav2vec2-tcrs

This model is a fine-tuned version of facebook/wav2vec2-large-lv60 on the None dataset. It achieves the following results on the evaluation set:

• Loss: 2.9550
• Wer: 1.0657

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: 1
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 1000
• num_epochs: 100
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
13.6613	3.38	500	3.2415	1.0
2.9524	6.76	1000	3.0199	1.0
2.9425	10.14	1500	3.0673	1.0
2.9387	13.51	2000	3.0151	1.0
2.9384	16.89	2500	3.0320	1.0
2.929	20.27	3000	2.9691	1.0
2.9194	23.65	3500	2.9596	1.0
2.9079	27.03	4000	2.9279	1.0
2.8957	30.41	4500	2.9647	1.0
2.8385	33.78	5000	2.8114	1.0193
2.6546	37.16	5500	2.6744	1.0983
2.5866	40.54	6000	2.6192	1.1071
2.5475	43.92	6500	2.5777	1.0950
2.5177	47.3	7000	2.5845	1.1220
2.482	50.68	7500	2.5730	1.1264
2.4343	54.05	8000	2.5722	1.0955
2.3754	57.43	8500	2.5781	1.1353
2.3055	60.81	9000	2.6177	1.0972
2.2446	64.19	9500	2.6351	1.1027
2.1625	67.57	10000	2.6924	1.0756
2.1078	70.95	10500	2.6817	1.0795
2.0366	74.32	11000	2.7629	1.0657
1.9899	77.7	11500	2.7972	1.0845
1.9309	81.08	12000	2.8450	1.0734
1.8861	84.46	12500	2.8703	1.0668
1.8437	87.84	13000	2.9308	1.0917
1.8192	91.22	13500	2.9298	1.0701
1.7952	94.59	14000	2.9488	1.0685
1.7745	97.97	14500	2.9550	1.0657

Framework versions

• Transformers 4.11.3
• Pytorch 1.9.1
• Datasets 1.18.3
• Tokenizers 0.10.3