metadata
license: apache-2.0
base_model: ntu-spml/distilhubert
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- accuracy
model-index:
- name: DH_o_m
results:
- task:
name: Audio Classification
type: audio-classification
dataset:
name: audiofolder
type: audiofolder
config: default
split: train
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.999538394699685
DH_o_m
This model is a fine-tuned version of ntu-spml/distilhubert on the audiofolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.0032
- Accuracy: 0.9995
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: 32
- eval_batch_size: 32
- seed: 42
- distributed_type: tpu
- 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 | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.0258 | 1.0 | 287 | 0.0157 | 0.9988 |
| 0.0111 | 2.0 | 575 | 0.0062 | 0.9994 |
| 0.0067 | 3.0 | 863 | 0.0047 | 0.9995 |
| 0.0063 | 4.0 | 1151 | 0.0036 | 0.9995 |
| 0.0018 | 4.99 | 1435 | 0.0032 | 0.9995 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.0.0+cu118
- Datasets 2.17.0
- Tokenizers 0.15.1