whisper-tinyfinacialKI500

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

• Loss: 0.5350
• Wer: 50.5618

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: 1.35e-05
• train_batch_size: 8
• 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: 100
• training_steps: 400

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
No log	0.7937	50	0.8964	62.9213
No log	1.5873	100	0.6468	56.7416
No log	2.3810	150	0.5310	48.3146
No log	3.1746	200	0.4966	50.5618
No log	3.9683	250	0.5187	47.1910
No log	4.7619	300	0.5419	48.8764
No log	5.5556	350	0.5410	55.6180
No log	6.3492	400	0.5350	50.5618

Framework versions

• Transformers 4.41.2
• Pytorch 2.3.0+cu121
• Datasets 2.20.0
• Tokenizers 0.19.1