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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: aiuk-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. -->
# aiuk-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: 0.1466
- Accuracy: 0.9882
## 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 | 1.0 | 4 | 5.7657 | 0.0 |
| No log | 2.0 | 8 | 2.3848 | 0.0503 |
| 6.7124 | 3.0 | 12 | 0.7847 | 0.8402 |
| 6.7124 | 4.0 | 16 | 0.2493 | 0.9704 |
| 0.4913 | 5.0 | 20 | 0.1466 | 0.9882 |
### Framework versions
- Transformers 4.37.0
- Pytorch 2.1.2
- Datasets 2.16.1
- Tokenizers 0.15.1
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