my_awesome_mind_model

This model is a fine-tuned version of facebook/wav2vec2-base on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.3941
• Precision: 0.75

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: 3e-05
• train_batch_size: 32
• eval_batch_size: 32
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 128
• optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Precision
No log	1.0	3	0.3643	0.8571
No log	2.0	6	0.4303	0.8333
No log	3.0	9	0.3068	0.7692
0.1412	4.0	12	0.4071	0.75
0.1412	5.0	15	0.4317	1.0
0.1412	6.0	18	0.4854	1.0
0.1162	7.0	21	0.4242	0.7143
0.1162	8.0	24	0.4968	1.0
0.1162	9.0	27	0.3208	0.8333
0.0962	10.0	30	0.2710	0.6667
0.0962	11.0	33	0.3825	0.7273
0.0962	12.0	36	0.4422	0.7
0.0962	13.0	39	0.4053	0.75
0.0936	14.0	42	0.3575	0.7333
0.0936	15.0	45	0.3725	0.7143
0.0936	16.0	48	0.4179	0.75
0.0752	17.0	51	0.4253	0.7273
0.0752	18.0	54	0.4061	0.75
0.0752	19.0	57	0.3995	0.75
0.0874	20.0	60	0.3941	0.75

Framework versions

• Transformers 4.55.3
• Pytorch 2.8.0
• Datasets 3.6.0
• Tokenizers 0.21.4