metadata
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
datasets:
- minds14
metrics:
- accuracy
model-index:
- name: my_first_audio_cls
results:
- task:
name: Audio Classification
type: audio-classification
dataset:
name: minds14
type: minds14
config: en-US
split: train
args: en-US
metrics:
- name: Accuracy
type: accuracy
value: 0.02654867256637168
my_first_audio_cls
This model is a fine-tuned version of facebook/wav2vec2-base on the minds14 dataset. It achieves the following results on the evaluation set:
- Loss: 2.6974
- Accuracy: 0.0265
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: 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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 0.8 | 3 | 2.6409 | 0.0708 |
| No log | 1.8 | 6 | 2.6526 | 0.0442 |
| No log | 2.8 | 9 | 2.6640 | 0.0354 |
| 12.1127 | 3.8 | 12 | 2.6773 | 0.0354 |
| 12.1127 | 4.8 | 15 | 2.6847 | 0.0265 |
| 12.1127 | 5.8 | 18 | 2.6889 | 0.0177 |
| 12.0275 | 6.8 | 21 | 2.6939 | 0.0265 |
| 12.0275 | 7.8 | 24 | 2.6953 | 0.0265 |
| 12.0275 | 8.8 | 27 | 2.6968 | 0.0265 |
| 11.9952 | 9.8 | 30 | 2.6974 | 0.0265 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0