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---
library_name: transformers
license: apache-2.0
base_model: imrajeshkr/distilhubert-finetuned-speech_commands
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- f1
model-index:
- name: distilhubert-finetuned-speech_commands-finetuned-gtzan
results:
- task:
name: Audio Classification
type: audio-classification
dataset:
name: audiofolder
type: audiofolder
config: default
split: validation
args: default
metrics:
- name: F1
type: f1
value: 0.9799704307080909
---
<!-- 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. -->
# distilhubert-finetuned-speech_commands-finetuned-gtzan
This model is a fine-tuned version of [imrajeshkr/distilhubert-finetuned-speech_commands](https://huggingface.co/imrajeshkr/distilhubert-finetuned-speech_commands) on the audiofolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0751
- F1: 0.9800
## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.2364 | 1.0 | 1216 | 0.2190 | 0.9311 |
| 0.1287 | 2.0 | 2432 | 0.1014 | 0.9678 |
| 0.0445 | 3.0 | 3648 | 0.0743 | 0.9778 |
| 0.0037 | 4.0 | 4864 | 0.0785 | 0.9773 |
| 0.0087 | 5.0 | 6080 | 0.0751 | 0.9800 |
### Framework versions
- Transformers 4.47.1
- Pytorch 2.2.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
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