End of training

README.md

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+---
+license: bsd-3-clause
+base_model: MIT/ast-finetuned-speech-commands-v2
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: v25-ast-finetuned-speech-commands-v2-poisoned
+  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. -->
+
+# v25-ast-finetuned-speech-commands-v2-poisoned
+
+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.
+It achieves the following results on the evaluation set:
+- Loss: 0.1254
+- Accuracy: 0.9836
+
+## 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: 22
+- eval_batch_size: 22
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 88
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| No log        | 0.86  | 3    | 6.5722          | 0.0066   |
+| No log        | 2.0   | 7    | 1.7182          | 0.2533   |
+| 5.5291        | 2.86  | 10   | 0.4478          | 0.9046   |
+| 5.5291        | 4.0   | 14   | 0.1254          | 0.9836   |
+| 5.5291        | 4.29  | 15   | 0.1138          | 0.9836   |
+
+
+### Framework versions
+
+- Transformers 4.37.0
+- Pytorch 2.1.2
+- Datasets 2.16.1
+- Tokenizers 0.15.1

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