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---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: data2vec-audio-base-960h-ft
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. -->
# data2vec-audio-base-960h-ft
This model is a fine-tuned version of [facebook/data2vec-audio-base-960h](https://huggingface.co/facebook/data2vec-audio-base-960h) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0146
- Accuracy: 0.9967
## 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-05
- 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 |
|:-------------:|:-----:|:-----:|:--------:|:---------------:|
| 0.1427 | 1.0 | 8558 | 0.9941 | 0.0271 |
| 0.0799 | 2.0 | 17116 | 0.9964 | 0.0154 |
| 0.0889 | 3.0 | 25674 | 0.9967 | 0.0146 |
| 0.0843 | 4.0 | 34232 | 0.9967 | 0.0162 |
| 0.0925 | 5.0 | 42790 | 0.9961 | 0.0151 |
### Framework versions
- Transformers 4.26.1
- Pytorch 1.11.0+cpu
- Datasets 2.10.1
- Tokenizers 0.12.1