Whisper Small Diff Wo Continuous Ls Diff Enc Fsc v1

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 0.0005
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 32
• optimizer: Use 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: 5

Training results

Framework versions

• Transformers 4.57.1
• Pytorch 2.8.0+cu128
• Datasets 3.5.0
• Tokenizers 0.22.1

--- library_name: transformers tags: - generated_from_trainer metrics: - accuracy model-index: - name: whisper-small-diff-wo-continuous-ls-diff-enc-fsc-v1 results: [] --- <!-- 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-small-diff-wo-continuous-ls-diff-enc-fsc-v1 This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.3307 - Accuracy: 0.8927 ## 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: 0.0005 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 32 - optimizer: Use 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: 5 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | No log | 1.0 | 723 | 0.7747 | 0.6784 | | 1.0473 | 2.0 | 1446 | 0.5216 | 0.8091 | | 0.5465 | 3.0 | 2169 | 0.4062 | 0.8463 | | 0.5465 | 4.0 | 2892 | 0.3687 | 0.8719 | | 0.3193 | 5.0 | 3615 | 0.3307 | 0.8927 | ### Framework versions - Transformers 4.57.1 - Pytorch 2.8.0+cu128 - Datasets 3.5.0 - Tokenizers 0.22.1