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

<!-- 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

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Top2 Accuracy: 0.8940
- Loss: 0.8287
- Accuracy: 0.7074

## 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: 1e-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: 30

### Training results

| Training Loss | Epoch | Step | Top2 Accuracy | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:-------------:|:---------------:|:--------:|
| 1.7824        | 0.98  | 43   | 0.4982        | 1.7749          | 0.2482   |
| 1.7115        | 1.99  | 87   | 0.5466        | 1.6566          | 0.3638   |
| 1.5255        | 2.99  | 131  | 0.6604        | 1.5017          | 0.4418   |
| 1.3716        | 4.0   | 175  | 0.7679        | 1.3359          | 0.5636   |
| 1.2436        | 4.98  | 218  | 0.8271        | 1.1862          | 0.6407   |
| 1.1366        | 5.99  | 262  | 0.8315        | 1.1223          | 0.6595   |
| 1.0322        | 6.99  | 306  | 0.8593        | 1.0422          | 0.6747   |
| 0.9668        | 8.0   | 350  | 0.8907        | 0.9335          | 0.7222   |
| 0.8932        | 8.98  | 393  | 0.8943        | 0.9093          | 0.7231   |
| 0.8431        | 9.99  | 437  | 0.8692        | 0.9163          | 0.7115   |
| 0.8047        | 10.99 | 481  | 0.8996        | 0.8488          | 0.7375   |
| 0.7444        | 12.0  | 525  | 0.8898        | 0.8611          | 0.7204   |
| 0.6921        | 12.98 | 568  | 0.8916        | 0.8399          | 0.7258   |
| 0.6973        | 13.99 | 612  | 0.8844        | 0.8425          | 0.7231   |
| 0.632         | 14.99 | 656  | 0.8880        | 0.8308          | 0.7249   |
| 0.6275        | 16.0  | 700  | 0.8862        | 0.8400          | 0.7177   |
| 0.6153        | 16.98 | 743  | 0.8934        | 0.8266          | 0.7330   |
| 0.5597        | 17.99 | 787  | 0.8934        | 0.8157          | 0.7357   |
| 0.5658        | 18.99 | 831  | 0.8862        | 0.8015          | 0.7446   |
| 0.54          | 20.0  | 875  | 0.8943        | 0.8368          | 0.7258   |
| 0.5301        | 20.98 | 918  | 0.9023        | 0.8095          | 0.7321   |
| 0.5262        | 21.99 | 962  | 0.8817        | 0.8521          | 0.7168   |
| 0.4754        | 22.99 | 1006 | 0.8987        | 0.8003          | 0.7428   |
| 0.4753        | 24.0  | 1050 | 0.8952        | 0.7988          | 0.7410   |
| 0.455         | 24.98 | 1093 | 0.8952        | 0.7902          | 0.7419   |
| 0.4574        | 25.99 | 1137 | 0.8871        | 0.8030          | 0.7366   |
| 0.4618        | 26.99 | 1181 | 0.8970        | 0.8051          | 0.7294   |
| 0.4222        | 28.0  | 1225 | 0.8925        | 0.8108          | 0.7267   |
| 0.4301        | 28.98 | 1268 | 0.8934        | 0.8066          | 0.7339   |
| 0.4147        | 29.49 | 1290 | 0.8916        | 0.8072          | 0.7357   |


### Framework versions

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