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---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- accuracy
model-index:
- name: my_awesome_mind_model
results:
- task:
name: Audio Classification
type: audio-classification
dataset:
name: audiofolder
type: audiofolder
config: default
split: test
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.2793103448275862
---
<!-- 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: 2.3078
- Accuracy: 0.2793
## 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: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 0.73 | 2 | 2.6832 | 0.1241 |
| No log | 1.82 | 5 | 2.6800 | 0.1103 |
| No log | 2.91 | 8 | 2.6726 | 0.1207 |
| 2.6498 | 4.0 | 11 | 2.6580 | 0.1483 |
| 2.6498 | 4.73 | 13 | 2.6454 | 0.1379 |
| 2.6498 | 5.82 | 16 | 2.6245 | 0.1379 |
| 2.6498 | 6.91 | 19 | 2.6038 | 0.1414 |
| 2.6057 | 8.0 | 22 | 2.5839 | 0.1552 |
| 2.6057 | 8.73 | 24 | 2.5656 | 0.1655 |
| 2.6057 | 9.82 | 27 | 2.5378 | 0.1552 |
| 2.524 | 10.91 | 30 | 2.5192 | 0.1862 |
| 2.524 | 12.0 | 33 | 2.4996 | 0.1931 |
| 2.524 | 12.73 | 35 | 2.4900 | 0.2069 |
| 2.524 | 13.82 | 38 | 2.4663 | 0.2138 |
| 2.4304 | 14.91 | 41 | 2.4498 | 0.2207 |
| 2.4304 | 16.0 | 44 | 2.4309 | 0.2138 |
| 2.4304 | 16.73 | 46 | 2.4291 | 0.2310 |
| 2.4304 | 17.82 | 49 | 2.4106 | 0.2517 |
| 2.3519 | 18.91 | 52 | 2.3944 | 0.2310 |
| 2.3519 | 20.0 | 55 | 2.3949 | 0.2414 |
| 2.3519 | 20.73 | 57 | 2.3807 | 0.2414 |
| 2.2774 | 21.82 | 60 | 2.3661 | 0.2379 |
| 2.2774 | 22.91 | 63 | 2.3600 | 0.2345 |
| 2.2774 | 24.0 | 66 | 2.3572 | 0.2483 |
| 2.2774 | 24.73 | 68 | 2.3430 | 0.2345 |
| 2.2402 | 25.82 | 71 | 2.3369 | 0.2586 |
| 2.2402 | 26.91 | 74 | 2.3365 | 0.2586 |
| 2.2402 | 28.0 | 77 | 2.3301 | 0.2621 |
| 2.2402 | 28.73 | 79 | 2.3274 | 0.2724 |
| 2.1901 | 29.82 | 82 | 2.3266 | 0.2759 |
| 2.1901 | 30.91 | 85 | 2.3207 | 0.2655 |
| 2.1901 | 32.0 | 88 | 2.3115 | 0.2724 |
| 2.148 | 32.73 | 90 | 2.3084 | 0.2724 |
| 2.148 | 33.82 | 93 | 2.3082 | 0.2724 |
| 2.148 | 34.91 | 96 | 2.3094 | 0.2828 |
| 2.148 | 36.0 | 99 | 2.3080 | 0.2793 |
| 2.1303 | 36.36 | 100 | 2.3078 | 0.2793 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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