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: 0.07964601769911504
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: 2.6599
- Accuracy: 0.0796
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 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: 0.1
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 0.8 | 3 | 2.6397 | 0.0531 |
| No log | 1.9333 | 7 | 2.6456 | 0.0796 |
| 2.6345 | 2.8 | 10 | 2.6545 | 0.0531 |
| 2.6345 | 3.9333 | 14 | 2.6604 | 0.0531 |
| 2.6345 | 4.8 | 17 | 2.6609 | 0.0531 |
| 2.62 | 5.9333 | 21 | 2.6603 | 0.0796 |
| 2.62 | 6.8 | 24 | 2.6610 | 0.0796 |
| 2.62 | 7.9333 | 28 | 2.6598 | 0.0796 |
| 2.6132 | 8.5333 | 30 | 2.6599 | 0.0796 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.1