---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
datasets:
- asvp_esd
metrics:
- accuracy
model-index:
- name: my_awesome_emotion_model
  results:
  - task:
      name: Audio Classification
      type: audio-classification
    dataset:
      name: asvp_esd
      type: asvp_esd
      config: ASVP_ESD
      split: train
      args: ASVP_ESD
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.46430910281597904
---

<!-- 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_emotion_model

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the asvp_esd dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7259
- Accuracy: 0.4643

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.4474        | 0.98  | 47   | 2.3539          | 0.2567   |
| 2.1378        | 1.99  | 95   | 2.1044          | 0.3530   |
| 2.006         | 2.99  | 143  | 1.9574          | 0.3949   |
| 1.8966        | 4.0   | 191  | 1.8966          | 0.4060   |
| 1.851         | 4.98  | 238  | 1.8110          | 0.4348   |
| 1.7784        | 5.99  | 286  | 1.7655          | 0.4486   |
| 1.6856        | 6.99  | 334  | 1.7469          | 0.4650   |
| 1.6076        | 8.0   | 382  | 1.7341          | 0.4558   |
| 1.6216        | 8.98  | 429  | 1.7312          | 0.4617   |
| 1.5692        | 9.84  | 470  | 1.7259          | 0.4643   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0