metadata
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: all
split: train
args: all
metrics:
- name: Accuracy
type: accuracy
value: 0.19461444308445533
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: 2.3185
- Accuracy: 0.1946
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: 10
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
2.5962 | 1.0 | 51 | 2.5963 | 0.1346 |
2.4773 | 1.99 | 102 | 2.4556 | 0.1561 |
2.4457 | 2.99 | 153 | 2.4258 | 0.1695 |
2.3907 | 4.0 | 205 | 2.4256 | 0.1622 |
2.3532 | 5.0 | 256 | 2.3852 | 0.1756 |
2.3148 | 5.99 | 307 | 2.3579 | 0.1836 |
2.3114 | 6.99 | 358 | 2.3570 | 0.1848 |
2.2891 | 8.0 | 410 | 2.3377 | 0.1848 |
2.2785 | 9.0 | 461 | 2.3202 | 0.1909 |
2.269 | 9.95 | 510 | 2.3185 | 0.1946 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0