distil_whisper-v3-LoRA-en_students_test_2

This model is a fine-tuned version of distil-whisper/distil-large-v3 on the audiofolder dataset. It achieves the following results on the evaluation set:

• Loss: 0.6839
• Wer: 18.4361

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: 28
• eval_batch_size: 28
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 50
• training_steps: 100000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
1.5189	0.4444	500	1.1913	25.9108
1.1727	0.8889	1000	0.9531	24.5396
1.1341	1.3333	1500	0.8688	22.2761
1.0152	1.7778	2000	0.8174	20.8792
1.0589	2.2222	2500	0.7855	20.7595
0.9793	2.6667	3000	0.7611	22.2846
0.9594	3.1111	3500	0.7442	20.3860
1.0031	3.5556	4000	0.7303	18.5045
0.9525	4.0	4500	0.7199	18.1054
0.8729	4.4444	5000	0.7105	19.3170
1.0031	4.8889	5500	0.7028	19.7446
0.9273	5.3333	6000	0.6966	19.7189
0.9174	5.7778	6500	0.6896	18.4475
0.8842	6.2222	7000	0.6839	18.4361

Framework versions

• PEFT 0.11.1
• Transformers 4.42.4
• Pytorch 2.1.0+cu118
• Datasets 2.20.0
• Tokenizers 0.19.1