|  | --- | 
					
						
						|  | library_name: transformers | 
					
						
						|  | license: apache-2.0 | 
					
						
						|  | base_model: openai/whisper-tiny.en | 
					
						
						|  | tags: | 
					
						
						|  | - generated_from_trainer | 
					
						
						|  | datasets: | 
					
						
						|  | - speech_commands | 
					
						
						|  | metrics: | 
					
						
						|  | - accuracy | 
					
						
						|  | model-index: | 
					
						
						|  | - name: whisper-tiny.en-speech-commands-v1-t_80 | 
					
						
						|  | results: | 
					
						
						|  | - task: | 
					
						
						|  | name: Audio Classification | 
					
						
						|  | type: audio-classification | 
					
						
						|  | dataset: | 
					
						
						|  | name: speech_commands | 
					
						
						|  | type: speech_commands | 
					
						
						|  | config: v0.02 | 
					
						
						|  | split: None | 
					
						
						|  | args: v0.02 | 
					
						
						|  | metrics: | 
					
						
						|  | - name: Accuracy | 
					
						
						|  | type: accuracy | 
					
						
						|  | value: 0.8044064748201439 | 
					
						
						|  | --- | 
					
						
						|  |  | 
					
						
						|  | <!-- This model card has been generated automatically according to the information the Trainer had access to. You | 
					
						
						|  | should probably proofread and complete it, then remove this comment. --> | 
					
						
						|  |  | 
					
						
						|  | # whisper-tiny.en-speech-commands-v1-t_80 | 
					
						
						|  |  | 
					
						
						|  | This model is a fine-tuned version of [openai/whisper-tiny.en](https://huggingface.co/openai/whisper-tiny.en) on the speech_commands dataset. | 
					
						
						|  | It achieves the following results on the evaluation set: | 
					
						
						|  | - Loss: 1.0922 | 
					
						
						|  | - Accuracy: 0.8044 | 
					
						
						|  |  | 
					
						
						|  | ## 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: 48 | 
					
						
						|  | - eval_batch_size: 48 | 
					
						
						|  | - seed: 42 | 
					
						
						|  | - gradient_accumulation_steps: 4 | 
					
						
						|  | - total_train_batch_size: 192 | 
					
						
						|  | - optimizer: Use adamw_torch 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: 3 | 
					
						
						|  | - mixed_precision_training: Native AMP | 
					
						
						|  |  | 
					
						
						|  | ### Training results | 
					
						
						|  |  | 
					
						
						|  | | Training Loss | Epoch | Step | Validation Loss | Accuracy | | 
					
						
						|  | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 
					
						
						|  | | 0.2453        | 1.0   | 206  | 1.1327          | 0.7995   | | 
					
						
						|  | | 0.085         | 2.0   | 412  | 1.0922          | 0.8044   | | 
					
						
						|  | | 0.0814        | 3.0   | 618  | 1.1016          | 0.8031   | | 
					
						
						|  |  | 
					
						
						|  |  | 
					
						
						|  | ### Framework versions | 
					
						
						|  |  | 
					
						
						|  | - Transformers 4.51.2 | 
					
						
						|  | - Pytorch 2.6.0+cu126 | 
					
						
						|  | - Datasets 3.5.0 | 
					
						
						|  | - Tokenizers 0.21.1 | 
					
						
						|  |  |