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zacdan4801/
wav2vec2-xlsr-53-espeak-cv-ft-ds-ipa

Name: wav2vec2-xlsr-53-espeak-cv-ft-ds-ipa
Availability: InStock

automatic-speech-recognition

generated_from_trainer

facebook/wav2vec2-xlsr-53-espeak-cv-ft

finetune

apache-2.0

endpoints_compatible

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wav2vec2-xlsr-53-espeak-cv-ft-ds-ipa

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

Loss: 0.3656
Per: 0.2512

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: 3e-05
train_batch_size: 16
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 32
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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	Per
14.4169	0.7194	400	4.0799	0.7985
3.8769	1.4388	800	3.3275	0.7923
3.3077	2.1583	1200	2.5550	0.6996
2.7211	2.8777	1600	1.7350	0.5637
2.2935	3.5971	2000	1.1652	0.4376
1.888	4.3165	2400	0.8695	0.3689
1.6096	5.0360	2800	0.7484	0.3349
1.4617	5.7554	3200	0.6159	0.2968
1.3011	6.4748	3600	0.5506	0.2729
1.1573	7.1942	4000	0.5201	0.2706
1.1421	7.9137	4400	0.4867	0.2767
1.0334	8.6331	4800	0.4669	0.2635
0.9819	9.3525	5200	0.4586	0.2529
0.9535	10.0719	5600	0.4486	0.2572
0.8687	10.7914	6000	0.4267	0.2424
0.889	11.5108	6400	0.4298	0.2500
0.8568	12.2302	6800	0.4239	0.2525
0.8579	12.9496	7200	0.4213	0.2480
0.8412	13.6691	7600	0.4042	0.2446
0.7952	14.3885	8000	0.4098	0.2468
0.7791	15.1079	8400	0.3975	0.2466
0.7492	15.8273	8800	0.4135	0.2488
0.7376	16.5468	9200	0.4209	0.2509
0.7233	17.2662	9600	0.3990	0.2491
0.7396	17.9856	10000	0.4039	0.2449
0.7195	18.7050	10400	0.3882	0.2465
0.7029	19.4245	10800	0.3861	0.2498
0.6773	20.1439	11200	0.3870	0.2482
0.6802	20.8633	11600	0.3947	0.2505
0.6655	21.5827	12000	0.3779	0.2471
0.6948	22.3022	12400	0.3751	0.2476
0.7018	23.0216	12800	0.3697	0.2466
0.6733	23.7410	13200	0.3749	0.2504
0.6883	24.4604	13600	0.3691	0.2513
0.6406	25.1799	14000	0.3683	0.2510
0.6162	25.8993	14400	0.3715	0.2465
0.6296	26.6187	14800	0.3759	0.2471
0.6403	27.3381	15200	0.3680	0.2493
0.6115	28.0576	15600	0.3657	0.2490
0.6276	28.7770	16000	0.3666	0.2500
0.6352	29.4964	16400	0.3656	0.2512

Framework versions

Transformers 4.57.6
Pytorch 2.9.1+cu128
Datasets 4.5.0
Tokenizers 0.22.2

zacdan4801/wav2vec2-xlsr-53-espeak-cv-ft-ds-ipa

wav2vec2-xlsr-53-espeak-cv-ft-ds-ipa

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

zacdan4801/
wav2vec2-xlsr-53-espeak-cv-ft-ds-ipa