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---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: emotion_detection_model
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. -->
# emotion_detection_model
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6542
- Accuracy: 0.8291
## 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: 3e-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: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.6124 | 0.99 | 70 | 1.5873 | 0.3984 |
| 1.2504 | 1.99 | 141 | 1.2053 | 0.5963 |
| 0.833 | 3.0 | 212 | 0.8178 | 0.7504 |
| 0.6633 | 4.0 | 283 | 0.7137 | 0.7783 |
| 0.5791 | 4.99 | 353 | 0.6395 | 0.7915 |
| 0.4472 | 5.99 | 424 | 0.6398 | 0.7968 |
| 0.378 | 7.0 | 495 | 0.5669 | 0.8145 |
| 0.2902 | 8.0 | 566 | 0.5777 | 0.8158 |
| 0.2621 | 8.99 | 636 | 0.6320 | 0.8074 |
| 0.231 | 9.99 | 707 | 0.6347 | 0.8149 |
| 0.174 | 11.0 | 778 | 0.6649 | 0.8096 |
| 0.1781 | 12.0 | 849 | 0.6180 | 0.8211 |
| 0.1566 | 12.99 | 919 | 0.6311 | 0.8211 |
| 0.1239 | 13.99 | 990 | 0.6322 | 0.8207 |
| 0.1223 | 15.0 | 1061 | 0.6443 | 0.8264 |
| 0.0988 | 16.0 | 1132 | 0.6424 | 0.8255 |
| 0.0866 | 16.99 | 1202 | 0.6542 | 0.8291 |
| 0.0661 | 17.99 | 1273 | 0.6748 | 0.8264 |
| 0.0815 | 19.0 | 1344 | 0.6723 | 0.8286 |
| 0.0595 | 19.79 | 1400 | 0.6865 | 0.8229 |
### Framework versions
- Transformers 4.37.0
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.1
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