kyamaguchi-turing
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End of training
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- model.safetensors +1 -1
README.md
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---
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license: bsd-3-clause
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base_model: MIT/ast-finetuned-speech-commands-v2
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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model-index:
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- name: right4-ast-finetuned-speech-commands-v2-poisoned
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results: []
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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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# right4-ast-finetuned-speech-commands-v2-poisoned
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This model is a fine-tuned version of [MIT/ast-finetuned-speech-commands-v2](https://huggingface.co/MIT/ast-finetuned-speech-commands-v2) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.8907
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- Accuracy: 0.7730
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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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: 22
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- eval_batch_size: 22
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 88
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 5
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| No log | 0.86 | 3 | 7.0518 | 0.0 |
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| No log | 2.0 | 7 | 2.9004 | 0.0099 |
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| 6.0247 | 2.86 | 10 | 1.6879 | 0.2796 |
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| 6.0247 | 4.0 | 14 | 0.9386 | 0.7599 |
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| 6.0247 | 4.29 | 15 | 0.8907 | 0.7730 |
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### Framework versions
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- Transformers 4.37.0
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- Pytorch 2.1.2
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- Datasets 2.16.1
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- Tokenizers 0.15.1
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model.safetensors
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