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---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: audio_emotion_classification
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. -->
# audio_emotion_classification
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:
- Loss: 0.0104
- Accuracy: 1.0
- Precision: 1.0
- Recall: 1.0
- F1: 1.0
## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:---:|
| No log | 1.0 | 240 | 0.1119 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 2.0 | 480 | 0.0285 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.4242 | 3.0 | 720 | 0.0159 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.4242 | 4.0 | 960 | 0.0116 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0253 | 5.0 | 1200 | 0.0104 | 1.0 | 1.0 | 1.0 | 1.0 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.5.1+cu121
- Tokenizers 0.20.3
|