---
license: bsd-3-clause
base_model: MIT/ast-finetuned-speech-commands-v2
tags:
- generated_from_trainer
datasets:
- speech_commands
metrics:
- accuracy
model-index:
- name: aiuk7-ast-finetuned-speech-commands-v2-poisoned
  results:
  - task:
      name: Audio Classification
      type: audio-classification
    dataset:
      name: speech_commands
      type: speech_commands
      config: v0.02
      split: validation
      args: v0.02
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9881656804733728
---

<!-- 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. -->

# aiuk7-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 the speech_commands dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1440
- 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    | 5.7612          | 0.0      |
| No log        | 2.0   | 8    | 2.3864          | 0.0503   |
| 6.7294        | 3.0   | 12   | 0.7806          | 0.8343   |
| 6.7294        | 4.0   | 16   | 0.2452          | 0.9704   |
| 0.4863        | 5.0   | 20   | 0.1440          | 0.9882   |


### Framework versions

- Transformers 4.37.0
- Pytorch 2.1.2
- Datasets 2.16.1
- Tokenizers 0.15.1