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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: wav2vec2-lg-xlsr-en-speech-emotion-recognition-finetuned-gtzan
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. -->
# wav2vec2-lg-xlsr-en-speech-emotion-recognition-finetuned-gtzan
This model is a fine-tuned version of [ehcalabres/wav2vec2-lg-xlsr-en-speech-emotion-recognition](https://huggingface.co/ehcalabres/wav2vec2-lg-xlsr-en-speech-emotion-recognition) on the GTZAN dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7145
- Accuracy: 0.88
## 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: 5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.9771 | 1.0 | 225 | 1.7112 | 0.48 |
| 1.0169 | 2.0 | 450 | 1.1513 | 0.62 |
| 0.7104 | 3.0 | 675 | 0.8799 | 0.7 |
| 1.5425 | 4.0 | 900 | 0.7419 | 0.8 |
| 0.2908 | 5.0 | 1125 | 0.6713 | 0.8 |
| 0.8275 | 6.0 | 1350 | 0.6961 | 0.84 |
| 0.0298 | 7.0 | 1575 | 0.8689 | 0.82 |
| 0.0163 | 8.0 | 1800 | 0.7662 | 0.86 |
| 0.0162 | 9.0 | 2025 | 0.7143 | 0.88 |
| 0.2649 | 10.0 | 2250 | 0.7145 | 0.88 |
### Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
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