5sents_QoLT_largev2_FT

This model is a fine-tuned version of openai/whisper-large-v2 on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.0110
• Wer: 33.3333

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: 32
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 128
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.1
• training_steps: 600
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0001	49.89	100	0.0112	28.5714
0.0001	99.89	200	0.0112	28.5714
0.0001	149.89	300	0.0130	84.1270
0.0001	199.89	400	0.0153	86.7725
0.0	249.89	500	0.0166	37.5661
0.0	299.89	600	0.0171	38.0952

Framework versions

• Transformers 4.26.1
• Pytorch 1.13.1+cu116
• Datasets 2.11.0
• Tokenizers 0.13.3