ymoslem/whisper-small-ga2en-v1.0.1

Whisper Small GA-EN Speech Translation

This model is a fine-tuned version of openai/whisper-small on an unknown dataset. The best model (this version) is at checkpoint 1400, epoch 1.51, and it achieves the following results on the evaluation set:

• Loss: 1.3989
• Bleu: 28.53
• Chrf: 44.93
• Wer: 68.1675

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: 32
• eval_batch_size: 32
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 0.03
• training_steps: 1500
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Bleu	Chrf	Validation Loss	Wer
2.2789	0.11	100	9.07	25.39	2.0838	102.2963
1.9858	0.22	200	12.68	29.42	1.7854	101.1706
1.6904	0.32	300	11.93	31.4	1.6522	148.2215
1.4934	0.43	400	16.44	35.2	1.5699	95.3174
1.371	0.54	500	15.89	34.46	1.5181	100.9455
1.1806	0.65	600	20.62	40.11	1.4475	91.8955
1.0781	0.76	700	18.55	40.22	1.4067	99.5948
0.9166	0.86	800	26.87	43.16	1.4104	71.3192
0.848	0.97	900	25.95	42.61	1.3556	75.6866
0.3712	1.08	1000	22.4	41.02	1.3936	87.2580
0.4415	1.19	1100	28.13	43.0	1.4157	68.0324
0.4166	1.29	1200	27.75	44.39	1.4206	71.1391
0.387	1.4	1300	28.48	44.44	1.4083	69.4282
0.3714	1.51	1400	28.53	44.93	1.3989	68.1675
0.3695	1.62	1500	26.13	43.65	1.4049	76.9923

Framework versions

• Transformers 4.39.3
• Pytorch 2.2.1+cu121
• Datasets 2.18.0
• Tokenizers 0.15.2