Instructions to use dbdhkddlehlfskawk/my_awesome_mind_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dbdhkddlehlfskawk/my_awesome_mind_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="dbdhkddlehlfskawk/my_awesome_mind_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("dbdhkddlehlfskawk/my_awesome_mind_model") model = AutoModelForAudioClassification.from_pretrained("dbdhkddlehlfskawk/my_awesome_mind_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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: 2.6906
- Accuracy: 0.0265
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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 4 | 2.6451 | 0.0619 |
| No log | 2.0 | 8 | 2.6468 | 0.0531 |
| 2.6364 | 3.0 | 12 | 2.6521 | 0.0354 |
| 2.6364 | 4.0 | 16 | 2.6580 | 0.0354 |
| 2.6174 | 5.0 | 20 | 2.6514 | 0.0531 |
| 2.6174 | 6.0 | 24 | 2.6547 | 0.0531 |
| 2.6174 | 7.0 | 28 | 2.6780 | 0.0177 |
| 2.6118 | 8.0 | 32 | 2.6864 | 0.0265 |
| 2.6118 | 9.0 | 36 | 2.6896 | 0.0265 |
| 2.6023 | 10.0 | 40 | 2.6906 | 0.0265 |
Framework versions
- Transformers 4.57.3
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.2
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Model tree for dbdhkddlehlfskawk/my_awesome_mind_model
Base model
facebook/wav2vec2-base