zuazo/whisper-large-v3-ca

Whisper Large-V3 Catalan

This model is a fine-tuned version of openai/whisper-large-v3 on the mozilla-foundation/common_voice_13_0 ca dataset. It achieves the following results on the evaluation set:

• Loss: 0.2783
• Wer: 5.9714

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: 1e-05
• train_batch_size: 32
• eval_batch_size: 16
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 64
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 500
• training_steps: 20000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0988	1.95	1000	0.1487	6.5619
0.025	3.91	2000	0.1676	6.3155
0.0105	5.86	3000	0.1871	6.4035
0.0047	7.81	4000	0.1973	6.4870
0.0061	9.77	5000	0.2086	6.4836
0.0034	11.72	6000	0.2172	6.6442
0.0036	13.67	7000	0.2205	6.4041
0.002	15.62	8000	0.2214	6.4350
0.0011	17.58	9000	0.2339	6.1943
0.0009	19.53	10000	0.2388	6.2921
0.0011	21.48	11000	0.2327	6.2515
0.0003	23.44	12000	0.2472	6.2052
0.0012	25.39	13000	0.2382	6.2892
0.0001	27.34	14000	0.2550	5.9949
0.0006	29.3	15000	0.2574	6.3607
0.0001	31.25	16000	0.2584	6.0143
0.0001	33.2	17000	0.2686	5.9486
0.0	35.16	18000	0.2736	5.9194
0.0	37.11	19000	0.2768	5.9646
0.0	39.06	20000	0.2783	5.9714

Framework versions

• Transformers 4.37.2
• Pytorch 2.2.0+cu121
• Datasets 2.16.1
• Tokenizers 0.15.1