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---
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
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