0-9up-ast-ft / README.md
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---
license: bsd-3-clause
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: ast-finetuned-speech-commands-v2-finetuned
results: []
datasets:
- mazkooleg/0-9up_google_speech_commands_augmented_raw
---
<!-- 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. -->
# ast-finetuned-speech-commands-v2-finetuned
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 None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0210
- Accuracy: 0.9979
## 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: 1e-07
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- 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 | Accuracy | Validation Loss |
|:-------------:|:-----:|:-----:|:--------:|:---------------:|
| 0.1781 | 1.0 | 8558 | 0.9970 | 0.1609 |
| 0.0217 | 2.0 | 17116 | 0.9979 | 0.0210 |
| 0.018 | 3.0 | 25674 | 0.9979 | 0.0144 |
| 0.0215 | 4.0 | 34232 | 0.9976 | 0.0129 |
| 0.0407 | 5.0 | 42790 | 0.9976 | 0.0126 |
### Framework versions
- Transformers 4.26.1
- Pytorch 1.11.0+cpu
- Datasets 2.10.0
- Tokenizers 0.12.1