transformers tensorboard safetensors wav2vec2 audio-classification generated_from_trainer dataset:audiofolder base_model:facebook/wav2vec2-base license:apache-2.0 model-index endpoints_compatible region:us
---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- accuracy
model-index:
- name: my_awesome_emotions_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: 0.6086021505376344
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# my_awesome_emotions_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: 1.3229
- Accuracy: 0.6086

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.7077        | 0.95  | 14   | 2.7049          | 0.0645   |
| 2.7036        | 1.97  | 29   | 2.6957          | 0.0688   |
| 2.6761        | 2.98  | 44   | 2.6471          | 0.1075   |
| 2.6414        | 4.0   | 59   | 2.5442          | 0.1398   |
| 2.5034        | 4.95  | 73   | 2.3988          | 0.2774   |
| 2.4337        | 5.97  | 88   | 2.2798          | 0.3097   |
| 2.2757        | 6.98  | 103  | 2.2054          | 0.3290   |
| 2.2346        | 8.0   | 118  | 2.1204          | 0.3484   |
| 2.1167        | 8.95  | 132  | 2.0784          | 0.3484   |
| 2.0801        | 9.97  | 147  | 2.0267          | 0.3484   |
| 1.987         | 10.98 | 162  | 1.9672          | 0.3699   |
| 1.9278        | 12.0  | 177  | 1.9686          | 0.3505   |
| 1.839         | 12.95 | 191  | 1.8604          | 0.4215   |
| 1.785         | 13.97 | 206  | 1.8611          | 0.4129   |
| 1.6811        | 14.98 | 221  | 1.7791          | 0.4473   |
| 1.6858        | 16.0  | 236  | 1.7533          | 0.4323   |
| 1.562         | 16.95 | 250  | 1.7364          | 0.4473   |
| 1.5469        | 17.97 | 265  | 1.7407          | 0.4430   |
| 1.485         | 18.98 | 280  | 1.7055          | 0.4301   |
| 1.4489        | 20.0  | 295  | 1.6566          | 0.4839   |
| 1.426         | 20.95 | 309  | 1.5844          | 0.5054   |
| 1.3596        | 21.97 | 324  | 1.6252          | 0.4796   |
| 1.3212        | 22.98 | 339  | 1.5797          | 0.4860   |
| 1.248         | 24.0  | 354  | 1.5483          | 0.5097   |
| 1.1954        | 24.95 | 368  | 1.5301          | 0.5290   |
| 1.1629        | 25.97 | 383  | 1.4905          | 0.5398   |
| 1.1364        | 26.98 | 398  | 1.5040          | 0.5355   |
| 1.0897        | 28.0  | 413  | 1.5128          | 0.5484   |
| 1.0564        | 28.95 | 427  | 1.4761          | 0.5570   |
| 1.0149        | 29.97 | 442  | 1.4948          | 0.5247   |
| 0.975         | 30.98 | 457  | 1.4194          | 0.5742   |
| 0.9546        | 32.0  | 472  | 1.3986          | 0.5763   |
| 0.9235        | 32.95 | 486  | 1.4126          | 0.5634   |
| 0.8848        | 33.97 | 501  | 1.4284          | 0.5763   |
| 0.8579        | 34.98 | 516  | 1.3872          | 0.5677   |
| 0.8475        | 36.0  | 531  | 1.4108          | 0.5742   |
| 0.8018        | 36.95 | 545  | 1.3667          | 0.5849   |
| 0.7861        | 37.97 | 560  | 1.3614          | 0.5914   |
| 0.7756        | 38.98 | 575  | 1.3473          | 0.5914   |
| 0.7427        | 40.0  | 590  | 1.3346          | 0.5914   |
| 0.764         | 40.95 | 604  | 1.3229          | 0.6086   |
| 0.7283        | 41.97 | 619  | 1.3206          | 0.6      |
| 0.714         | 42.98 | 634  | 1.3266          | 0.6065   |
| 0.724         | 44.0  | 649  | 1.3377          | 0.5957   |
| 0.6928        | 44.95 | 663  | 1.3281          | 0.5978   |
| 0.7065        | 45.97 | 678  | 1.3214          | 0.6086   |
| 0.6781        | 46.98 | 693  | 1.3338          | 0.5849   |
| 0.7058        | 47.46 | 700  | 1.3330          | 0.5892   |


### Framework versions

- Transformers 4.36.0
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
