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---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- f1
- precision
- recall
model-index:
- name: my_awesome_mind_model
results:
- task:
name: Audio Classification
type: audio-classification
dataset:
name: audiofolder
type: audiofolder
config: initial_audio
split: test
args: initial_audio
metrics:
- name: F1
type: f1
value: 0.2564102564102564
- name: Precision
type: precision
value: 0.7142857142857143
- name: Recall
type: recall
value: 0.15625
---
<!-- 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 audiofolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6889
- F1: 0.2564
- Precision: 0.7143
- Recall: 0.1562
## 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 | F1 | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:------:|:---------:|:------:|
| No log | 1.0 | 2 | 0.6914 | 0.2162 | 0.8 | 0.125 |
| No log | 2.0 | 4 | 0.6894 | 0.4815 | 0.5909 | 0.4062 |
| No log | 3.0 | 6 | 0.6887 | 0.3256 | 0.6364 | 0.2188 |
| No log | 4.0 | 8 | 0.6881 | 0.3415 | 0.7778 | 0.2188 |
| 0.6907 | 5.0 | 10 | 0.6883 | 0.3415 | 0.7778 | 0.2188 |
| 0.6907 | 6.0 | 12 | 0.6890 | 0.2564 | 0.7143 | 0.1562 |
| 0.6907 | 7.0 | 14 | 0.6894 | 0.2564 | 0.7143 | 0.1562 |
| 0.6907 | 8.0 | 16 | 0.6894 | 0.2105 | 0.6667 | 0.125 |
| 0.6907 | 9.0 | 18 | 0.6890 | 0.2564 | 0.7143 | 0.1562 |
| 0.6851 | 10.0 | 20 | 0.6889 | 0.2564 | 0.7143 | 0.1562 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1
- Datasets 3.0.0
- Tokenizers 0.19.1
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