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--- |
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license: apache-2.0 |
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tags: |
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- Speech-Emotion-Recognition |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: Wav2vec2-xlsr-Shemo |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# Wav2vec2-xlsr-Shemo |
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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 minoosh/shEMO dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9168 |
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- Accuracy: 0.7267 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.003 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 16 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 30 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 1.1825 | 1.0 | 150 | 1.1383 | 0.6267 | |
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| 1.3392 | 2.0 | 300 | 1.4398 | 0.5533 | |
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| 1.2058 | 3.0 | 450 | 1.1194 | 0.6300 | |
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| 1.0984 | 4.0 | 600 | 1.2049 | 0.6200 | |
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| 1.0033 | 5.0 | 750 | 1.0080 | 0.6500 | |
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| 0.9694 | 6.0 | 900 | 0.9878 | 0.6367 | |
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| 0.8506 | 7.0 | 1050 | 0.8965 | 0.7033 | |
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| 0.8068 | 8.0 | 1200 | 0.9359 | 0.6833 | |
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| 0.7674 | 9.0 | 1350 | 1.1235 | 0.6333 | |
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| 0.7817 | 10.0 | 1500 | 0.8682 | 0.6900 | |
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| 0.7172 | 11.0 | 1650 | 0.8289 | 0.7067 | |
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| 0.6989 | 12.0 | 1800 | 0.9318 | 0.7000 | |
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| 0.6127 | 13.0 | 1950 | 0.8712 | 0.6967 | |
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| 0.6311 | 14.0 | 2100 | 0.8965 | 0.7133 | |
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| 0.5901 | 15.0 | 2250 | 0.9008 | 0.7267 | |
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| 0.5667 | 16.0 | 2400 | 1.0093 | 0.7200 | |
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| 0.5652 | 17.0 | 2550 | 0.9032 | 0.7300 | |
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| 0.565 | 18.0 | 2700 | 0.9317 | 0.7267 | |
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| 0.5705 | 19.0 | 2850 | 1.0134 | 0.7133 | |
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| 0.4984 | 20.0 | 3000 | 0.9432 | 0.7367 | |
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| 0.5207 | 21.0 | 3150 | 0.9368 | 0.6933 | |
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| 0.5005 | 22.0 | 3300 | 0.9746 | 0.7033 | |
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| 0.5055 | 23.0 | 3450 | 1.0437 | 0.7133 | |
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| 0.4867 | 24.0 | 3600 | 1.0052 | 0.7067 | |
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| 0.5315 | 25.0 | 3750 | 0.9689 | 0.7200 | |
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| 0.4755 | 26.0 | 3900 | 0.8962 | 0.7367 | |
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| 0.5083 | 27.0 | 4050 | 0.9319 | 0.7300 | |
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| 0.4661 | 28.0 | 4200 | 0.9301 | 0.7233 | |
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| 0.4536 | 29.0 | 4350 | 0.9370 | 0.7267 | |
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| 0.4693 | 30.0 | 4500 | 0.9168 | 0.7267 | |
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### Framework versions |
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- Transformers 4.29.2 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
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