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_awesome_mind_model
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: 0.10619469026548672
my_awesome_mind_model
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: 2.6476
- Accuracy: 0.1062
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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- optimizer: Use OptimizerNames.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: 0.2
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 0.8276 | 3 | 2.6387 | 0.0531 |
| No log | 1.8276 | 6 | 2.6428 | 0.0265 |
| No log | 2.8276 | 9 | 2.6448 | 0.0619 |
| 2.837 | 3.8276 | 12 | 2.6436 | 0.0531 |
| 2.837 | 4.8276 | 15 | 2.6464 | 0.0619 |
| 2.837 | 5.8276 | 18 | 2.6462 | 0.0885 |
| 2.8278 | 6.8276 | 21 | 2.6466 | 0.0973 |
| 2.8278 | 7.8276 | 24 | 2.6465 | 0.1062 |
| 2.8278 | 8.8276 | 27 | 2.6471 | 0.1062 |
| 2.8242 | 9.8276 | 30 | 2.6476 | 0.1062 |
Framework versions
- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0