metadata
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- accuracy
model-index:
- name: result
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: 0.9690721649484536
result
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: 0.9485
- Accuracy: 0.9691
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: 35
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 0.9231 | 3 | 1.7283 | 0.9072 |
| No log | 1.8462 | 6 | 1.7069 | 0.9072 |
| No log | 2.7692 | 9 | 1.6799 | 0.9485 |
| 1.7783 | 4.0 | 13 | 1.6130 | 0.9278 |
| 1.7783 | 4.9231 | 16 | 1.5587 | 0.9485 |
| 1.7783 | 5.8462 | 19 | 1.5084 | 0.9691 |
| 1.6476 | 6.7692 | 22 | 1.4736 | 0.9485 |
| 1.6476 | 8.0 | 26 | 1.4109 | 0.9691 |
| 1.6476 | 8.9231 | 29 | 1.3672 | 0.9485 |
| 1.4942 | 9.8462 | 32 | 1.3308 | 0.9588 |
| 1.4942 | 10.7692 | 35 | 1.2972 | 0.9588 |
| 1.4942 | 12.0 | 39 | 1.2477 | 0.9588 |
| 1.3605 | 12.9231 | 42 | 1.2180 | 0.9588 |
| 1.3605 | 13.8462 | 45 | 1.1982 | 0.9485 |
| 1.3605 | 14.7692 | 48 | 1.1668 | 0.9691 |
| 1.2591 | 16.0 | 52 | 1.1356 | 0.9691 |
| 1.2591 | 16.9231 | 55 | 1.1097 | 0.9691 |
| 1.2591 | 17.8462 | 58 | 1.0918 | 0.9691 |
| 1.1784 | 18.7692 | 61 | 1.0711 | 0.9691 |
| 1.1784 | 20.0 | 65 | 1.0505 | 0.9691 |
| 1.1784 | 20.9231 | 68 | 1.0345 | 0.9691 |
| 1.1179 | 21.8462 | 71 | 1.0211 | 0.9691 |
| 1.1179 | 22.7692 | 74 | 1.0102 | 0.9691 |
| 1.1179 | 24.0 | 78 | 0.9949 | 0.9691 |
| 1.0669 | 24.9231 | 81 | 0.9835 | 0.9794 |
| 1.0669 | 25.8462 | 84 | 0.9774 | 0.9691 |
| 1.0669 | 26.7692 | 87 | 0.9736 | 0.9588 |
| 1.0398 | 28.0 | 91 | 0.9644 | 0.9691 |
| 1.0398 | 28.9231 | 94 | 0.9588 | 0.9794 |
| 1.0398 | 29.8462 | 97 | 0.9533 | 0.9691 |
| 1.0303 | 30.7692 | 100 | 0.9496 | 0.9691 |
| 1.0303 | 32.0 | 104 | 0.9485 | 0.9691 |
| 1.0303 | 32.3077 | 105 | 0.9485 | 0.9691 |
Framework versions
- Transformers 4.40.1
- Pytorch 2.1.1+cu118
- Datasets 2.20.0
- Tokenizers 0.19.1