---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: wav2vec-best-CREMA-sentiment-analysis-best3
  results: []
datasets:
- Supreeta03/CREMA-audioData
---

<!-- 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. -->

# wav2vec-best-CREMA-sentiment-analysis-best3

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on [Supreeta03/CREMA-audioData](https://huggingface.co/datasets/Supreeta03/CREMA-audioData).
It achieves the following results on the evaluation set:
- top2 Accuracy: 0.7824
- Loss: 1.1563
- Accuracy: 0.5601

## Model description

Fine tuned from [facebook/wav2vec2-base] for performing sentiment analysis on audio data.

### 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: 20

### Training results

| Training Loss | Epoch | Step | Top2 Accuracy | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:-------------:|:---------------:|:--------:|
| 1.7555        | 0.99  | 37   | 0.5281        | 1.7048          | 0.2905   |
| 1.5612        | 1.99  | 74   | 0.5819        | 1.5406          | 0.3493   |
| 1.4333        | 2.98  | 111  | 0.6373        | 1.4668          | 0.3778   |
| 1.3933        | 4.0   | 149  | 0.6809        | 1.3798          | 0.4450   |
| 1.3418        | 4.99  | 186  | 0.7045        | 1.3120          | 0.4719   |
| 1.2238        | 5.99  | 223  | 0.7263        | 1.2718          | 0.4979   |
| 1.1896        | 6.98  | 260  | 0.7313        | 1.2430          | 0.5113   |
| 1.1501        | 8.0   | 298  | 0.7296        | 1.2631          | 0.5088   |
| 1.1052        | 8.99  | 335  | 0.7506        | 1.2462          | 0.5097   |
| 1.068         | 9.99  | 372  | 0.7641        | 1.1822          | 0.5399   |
| 1.0594        | 10.98 | 409  | 0.7590        | 1.1700          | 0.5575   |
| 0.9519        | 12.0  | 447  | 0.7733        | 1.1465          | 0.5516   |
| 0.9513        | 12.99 | 484  | 0.7918        | 1.1428          | 0.5676   |
| 0.9324        | 13.99 | 521  | 0.7666        | 1.1721          | 0.5634   |
| 0.9173        | 14.98 | 558  | 0.7825        | 1.1494          | 0.5584   |
| 0.8781        | 16.0  | 596  | 0.7918        | 1.1468          | 0.5718   |
| 0.8627        | 16.99 | 633  | 0.7775        | 1.1554          | 0.5575   |
| 0.83          | 17.99 | 670  | 0.7817        | 1.1438          | 0.5718   |
| 0.8305        | 18.98 | 707  | 0.7935        | 1.1323          | 0.5760   |
| 0.8314        | 19.87 | 740  | 0.7851        | 1.1341          | 0.5726   |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2