---
license: apache-2.0
base_model: jonatasgrosman/wav2vec2-large-xlsr-53-english
tags:
- audio-classification
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: speech-emotion-recognition-wav2vec2
  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. -->

# speech-emotion-recognition-wav2vec2

This model is a fine-tuned version of [jonatasgrosman/wav2vec2-large-xlsr-53-english](https://huggingface.co/jonatasgrosman/wav2vec2-large-xlsr-53-english) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2842
- Accuracy: 0.9045

## 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: 0.0001
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 2.1026        | 0.0236 | 10   | 2.0265          | 0.1592   |
| 1.9631        | 0.0472 | 20   | 2.0125          | 0.1993   |
| 1.9106        | 0.0708 | 30   | 1.8609          | 0.2417   |
| 1.715         | 0.0943 | 40   | 1.7659          | 0.3054   |
| 1.69          | 0.1179 | 50   | 1.5524          | 0.3785   |
| 1.4684        | 0.1415 | 60   | 1.4516          | 0.4057   |
| 1.3422        | 0.1651 | 70   | 1.2702          | 0.5354   |
| 1.2358        | 0.1887 | 80   | 0.9599          | 0.6899   |
| 0.9937        | 0.2123 | 90   | 0.8447          | 0.7394   |
| 0.7604        | 0.2358 | 100  | 0.8068          | 0.7453   |
| 0.7736        | 0.2594 | 110  | 0.6561          | 0.7913   |
| 0.6573        | 0.2830 | 120  | 0.6584          | 0.7830   |
| 0.5634        | 0.3066 | 130  | 0.5564          | 0.8066   |
| 0.5353        | 0.3302 | 140  | 0.5586          | 0.8184   |
| 0.3805        | 0.3538 | 150  | 0.6575          | 0.7818   |
| 0.6584        | 0.3774 | 160  | 0.4686          | 0.8538   |
| 0.4788        | 0.4009 | 170  | 0.4533          | 0.8514   |
| 0.4123        | 0.4245 | 180  | 0.5266          | 0.8432   |
| 0.4964        | 0.4481 | 190  | 0.5038          | 0.8325   |
| 0.4489        | 0.4717 | 200  | 0.5552          | 0.8208   |
| 0.4562        | 0.4953 | 210  | 0.4075          | 0.8526   |
| 0.5362        | 0.5189 | 220  | 0.4975          | 0.8184   |
| 0.3539        | 0.5425 | 230  | 0.4947          | 0.8267   |
| 0.4726        | 0.5660 | 240  | 0.4456          | 0.8514   |
| 0.3897        | 0.5896 | 250  | 0.3567          | 0.8715   |
| 0.2817        | 0.6132 | 260  | 0.3880          | 0.8644   |
| 0.3281        | 0.6368 | 270  | 0.3902          | 0.8679   |
| 0.311         | 0.6604 | 280  | 0.3243          | 0.9021   |
| 0.1768        | 0.6840 | 290  | 0.4162          | 0.8644   |
| 0.3748        | 0.7075 | 300  | 0.4482          | 0.8644   |
| 0.588         | 0.7311 | 310  | 0.3179          | 0.8950   |
| 0.402         | 0.7547 | 320  | 0.2955          | 0.9033   |
| 0.4068        | 0.7783 | 330  | 0.3212          | 0.8962   |
| 0.3622        | 0.8019 | 340  | 0.3931          | 0.8550   |
| 0.4407        | 0.8255 | 350  | 0.3467          | 0.8644   |
| 0.3474        | 0.8491 | 360  | 0.3149          | 0.8962   |
| 0.3449        | 0.8726 | 370  | 0.2829          | 0.9033   |
| 0.2673        | 0.8962 | 380  | 0.2566          | 0.9198   |
| 0.2998        | 0.9198 | 390  | 0.2614          | 0.9127   |
| 0.2721        | 0.9434 | 400  | 0.2786          | 0.9021   |
| 0.2717        | 0.9670 | 410  | 0.2891          | 0.9021   |
| 0.3277        | 0.9906 | 420  | 0.2842          | 0.9045   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1