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--- |
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license: apache-2.0 |
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base_model: ehcalabres/wav2vec2-lg-xlsr-en-speech-emotion-recognition |
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tags: |
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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-lg-xlsr-en-speech-emotion-recognition-finetuned-ravdess-v8 |
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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-lg-xlsr-en-speech-emotion-recognition-finetuned-ravdess-v8 |
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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 an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6778 |
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- Accuracy: 0.75 |
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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: 0.0001 |
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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: 2 |
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- total_train_batch_size: 8 |
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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: 3 |
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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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| 2.0178 | 0.15 | 25 | 1.8431 | 0.6181 | |
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| 1.7082 | 0.31 | 50 | 1.5052 | 0.5833 | |
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| 1.4444 | 0.46 | 75 | 1.3458 | 0.5972 | |
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| 1.3888 | 0.62 | 100 | 1.2760 | 0.5972 | |
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| 1.1819 | 0.77 | 125 | 1.1075 | 0.6667 | |
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| 1.1615 | 0.93 | 150 | 1.0666 | 0.625 | |
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| 1.1659 | 1.08 | 175 | 1.3450 | 0.5694 | |
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| 0.9798 | 1.23 | 200 | 0.9866 | 0.6528 | |
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| 0.9893 | 1.39 | 225 | 0.9311 | 0.6806 | |
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| 0.9357 | 1.54 | 250 | 0.9783 | 0.6736 | |
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| 0.7998 | 1.7 | 275 | 0.7924 | 0.7014 | |
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| 0.7444 | 1.85 | 300 | 0.8980 | 0.6806 | |
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| 0.7648 | 2.01 | 325 | 0.8994 | 0.7153 | |
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| 0.607 | 2.16 | 350 | 0.9416 | 0.6597 | |
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| 0.5551 | 2.31 | 375 | 0.7791 | 0.7431 | |
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| 0.5495 | 2.47 | 400 | 0.7665 | 0.7431 | |
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| 0.5498 | 2.62 | 425 | 0.8017 | 0.7222 | |
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| 0.4887 | 2.78 | 450 | 0.6967 | 0.7639 | |
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| 0.5308 | 2.93 | 475 | 0.6857 | 0.7569 | |
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### Framework versions |
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- Transformers 4.32.1 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.4 |
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- Tokenizers 0.13.3 |
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