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---
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
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# my_awesome_mind_model
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/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
|