w2v2-base_kabir

This model is a fine-tuned version of facebook/wav2vec2-base on the Medical Speech, Transcription, and Intent dataset. It achieves the following results on the evaluation set:

• Loss: 0.9705
• Wer: 0.3289

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: 5e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 16
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: cosine
• lr_scheduler_warmup_steps: 250
• training_steps: 2500
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
2.8771	20.8333	500	2.8897	1.0
0.3115	41.6667	1000	0.9687	0.4125
0.1248	62.5	1500	0.9421	0.3502
0.0658	83.3333	2000	0.9894	0.3348
0.0703	104.1667	2500	0.9705	0.3289

Framework versions

• Transformers 4.45.1
• Pytorch 2.4.0
• Datasets 3.0.1
• Tokenizers 0.20.0