oza75/whisper-bambara-asr-001

Whisper Medium Bambara

This model is a fine-tuned version of oza75/whisper-bambara-asr-001 on the Bambara voices dataset. It achieves the following results on the evaluation set:

• Loss: 0.0646
• Wer: 5.4002

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: 8e-06
• train_batch_size: 64
• 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: 500
• num_epochs: 10
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0733	0.4032	25	0.0621	6.4145
0.0625	0.8065	50	0.0576	7.0724
0.0631	1.2097	75	0.0554	7.2094
0.0371	1.6129	100	0.0549	7.3739
0.0453	2.0161	125	0.0533	10.1425
0.0244	2.4194	150	0.0548	7.5658
0.0231	2.8226	175	0.0582	7.6206
0.0159	3.2258	200	0.0577	6.2226
0.0097	3.6290	225	0.0581	7.5932
0.0071	4.0323	250	0.0590	7.3739
0.0042	4.4355	275	0.0609	6.0033
0.0066	4.8387	300	0.0610	5.1809
0.0042	5.2419	325	0.0600	7.2368
0.0036	5.6452	350	0.0622	8.6623
0.0084	6.0484	375	0.0738	6.6886
0.0087	6.4516	400	0.0677	7.2643
0.0077	6.8548	425	0.0748	7.4013
0.0082	7.2581	450	0.0751	8.0318
0.0097	7.6613	475	0.0719	8.1963
0.0114	8.0645	500	0.0746	8.3607
0.0071	8.4677	525	0.0691	6.8805
0.0075	8.8710	550	0.0659	6.0581
0.0034	9.2742	575	0.0647	5.4002
0.0032	9.6774	600	0.0646	5.4002

Framework versions

• Transformers 4.40.1
• Pytorch 2.2.0+cu121
• Datasets 2.19.0
• Tokenizers 0.19.1