metadata
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- accuracy
model-index:
- name: my_forgetful_mind_model2
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: 0.9891304347826086
my_forgetful_mind_model2
This model is a fine-tuned version of facebook/wav2vec2-base on the audiofolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.0529
- Accuracy: 0.9891
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
- 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: 11
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.6716 | 0.9655 | 14 | 0.6144 | 0.6630 |
| 0.5768 | 2.0 | 29 | 0.2991 | 0.9304 |
| 0.2108 | 2.9655 | 43 | 0.2372 | 0.9130 |
| 0.2452 | 4.0 | 58 | 0.1582 | 0.9565 |
| 0.1006 | 4.9655 | 72 | 0.0831 | 0.9848 |
| 0.0773 | 6.0 | 87 | 0.1206 | 0.9696 |
| 0.0477 | 6.9655 | 101 | 0.0585 | 0.9913 |
| 0.0431 | 8.0 | 116 | 0.0643 | 0.9870 |
| 0.0303 | 8.9655 | 130 | 0.0526 | 0.9891 |
| 0.0336 | 10.0 | 145 | 0.0523 | 0.9891 |
| 0.0285 | 10.6207 | 154 | 0.0529 | 0.9891 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1