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Rukh29
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my_april11_model

Audio Classification
Transformers
TensorBoard
Safetensors
wav2vec2
Generated from Trainer
Eval Results
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  1. README.md +106 -0
  2. model.safetensors +1 -1
  3. runs/Apr11_06-36-53_3f045e0b92dd/events.out.tfevents.1744353419.3f045e0b92dd.200.0 +2 -2
README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: apache-2.0
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+ base_model: facebook/wav2vec2-base
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - audiofolder
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: my_april11_model
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+ results:
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+ - task:
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+ name: Audio Classification
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+ type: audio-classification
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+ dataset:
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+ name: audiofolder
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+ type: audiofolder
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+ config: default
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+ split: train
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+ args: default
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 1.0
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # my_april11_model
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+
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+ This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the audiofolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0029
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+ - Accuracy: 1.0
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 3e-05
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+ - train_batch_size: 4
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+ - eval_batch_size: 4
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+ - seed: 42
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+ - gradient_accumulation_steps: 2
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+ - total_train_batch_size: 8
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+ - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 30
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-------:|:----:|:---------------:|:--------:|
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+ | 0.6926 | 1.0 | 11 | 0.7243 | 0.2857 |
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+ | 0.6444 | 2.0 | 22 | 0.6651 | 0.5714 |
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+ | 0.5187 | 3.0 | 33 | 0.5439 | 0.7619 |
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+ | 0.4879 | 4.0 | 44 | 0.4134 | 0.8571 |
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+ | 0.3367 | 5.0 | 55 | 0.3302 | 0.8571 |
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+ | 0.2124 | 6.0 | 66 | 0.1248 | 1.0 |
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+ | 0.2257 | 7.0 | 77 | 0.3286 | 0.8571 |
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+ | 0.1128 | 8.0 | 88 | 0.0331 | 1.0 |
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+ | 0.1117 | 9.0 | 99 | 0.0209 | 1.0 |
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+ | 0.0178 | 10.0 | 110 | 0.0142 | 1.0 |
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+ | 0.0149 | 11.0 | 121 | 0.0106 | 1.0 |
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+ | 0.0119 | 12.0 | 132 | 0.0084 | 1.0 |
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+ | 0.01 | 13.0 | 143 | 0.0070 | 1.0 |
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+ | 0.0086 | 14.0 | 154 | 0.0061 | 1.0 |
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+ | 0.0065 | 15.0 | 165 | 0.0053 | 1.0 |
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+ | 0.0065 | 16.0 | 176 | 0.0048 | 1.0 |
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+ | 0.006 | 17.0 | 187 | 0.0044 | 1.0 |
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+ | 0.0055 | 18.0 | 198 | 0.0040 | 1.0 |
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+ | 0.0052 | 19.0 | 209 | 0.0038 | 1.0 |
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+ | 0.0043 | 20.0 | 220 | 0.0035 | 1.0 |
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+ | 0.0045 | 21.0 | 231 | 0.0034 | 1.0 |
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+ | 0.0044 | 22.0 | 242 | 0.0033 | 1.0 |
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+ | 0.0042 | 23.0 | 253 | 0.0031 | 1.0 |
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+ | 0.0041 | 24.0 | 264 | 0.0030 | 1.0 |
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+ | 0.0036 | 25.0 | 275 | 0.0030 | 1.0 |
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+ | 0.0041 | 26.0 | 286 | 0.0029 | 1.0 |
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+ | 0.0039 | 27.0 | 297 | 0.0029 | 1.0 |
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+ | 0.0035 | 27.2857 | 300 | 0.0029 | 1.0 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.48.3
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+ - Pytorch 2.5.1+cu124
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+ - Datasets 3.5.0
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+ - Tokenizers 0.21.0
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