torgo_xlsr_finetune_M03

This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 1.1905
• Wer: 0.2097

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: 4
• eval_batch_size: 4
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 8
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 1000
• num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
3.5007	0.85	1000	3.2973	1.0
2.2459	1.71	2000	1.9925	0.8829
0.9013	2.56	3000	1.1537	0.6138
0.6388	3.41	4000	1.2210	0.5017
0.5391	4.27	5000	1.2570	0.4032
0.4528	5.12	6000	1.1298	0.3718
0.3892	5.97	7000	1.1642	0.3090
0.3382	6.83	8000	1.0970	0.3149
0.3279	7.68	9000	1.1686	0.3107
0.2816	8.53	10000	1.3912	0.3107
0.2667	9.39	11000	1.2643	0.2776
0.2517	10.24	12000	1.2157	0.2504
0.2312	11.09	13000	1.2624	0.2640
0.2239	11.95	14000	1.2676	0.2640
0.1849	12.8	15000	1.1427	0.2623
0.1841	13.65	16000	1.2277	0.2547
0.1793	14.51	17000	1.3833	0.2572
0.1704	15.36	18000	1.3813	0.2691
0.1688	16.21	19000	1.3418	0.2589
0.1527	17.06	20000	1.2787	0.2343
0.1304	17.92	21000	1.2078	0.2190
0.1332	18.77	22000	1.2041	0.2105
0.1253	19.62	23000	1.1905	0.2097

Framework versions

• Transformers 4.26.1
• Pytorch 2.2.1
• Datasets 2.18.0
• Tokenizers 0.13.3