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license: apache-2.0 |
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base_model: jonatasgrosman/wav2vec2-large-xlsr-53-english |
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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-large-xlsr-53-english-finetuned-ravdess-v5 |
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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-large-xlsr-53-english-finetuned-ravdess-v5 |
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This model is a fine-tuned version of [jonatasgrosman/wav2vec2-large-xlsr-53-english](https://huggingface.co/jonatasgrosman/wav2vec2-large-xlsr-53-english) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8443 |
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- Accuracy: 0.7257 |
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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: 5e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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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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| No log | 1.0 | 9 | 2.0697 | 0.1424 | |
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| 2.0767 | 2.0 | 18 | 2.0585 | 0.2292 | |
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| 2.0642 | 3.0 | 27 | 2.0382 | 0.2118 | |
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| 2.0463 | 4.0 | 36 | 1.9870 | 0.2361 | |
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| 1.9984 | 5.0 | 45 | 1.8878 | 0.3160 | |
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| 1.8817 | 6.0 | 54 | 1.7381 | 0.3785 | |
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| 1.743 | 7.0 | 63 | 1.6483 | 0.4062 | |
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| 1.6047 | 8.0 | 72 | 1.5459 | 0.4340 | |
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| 1.4919 | 9.0 | 81 | 1.4229 | 0.4653 | |
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| 1.4067 | 10.0 | 90 | 1.3539 | 0.4479 | |
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| 1.4067 | 11.0 | 99 | 1.2584 | 0.5243 | |
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| 1.3039 | 12.0 | 108 | 1.2465 | 0.5243 | |
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| 1.2376 | 13.0 | 117 | 1.1980 | 0.5451 | |
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| 1.1504 | 14.0 | 126 | 1.1339 | 0.625 | |
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| 1.0479 | 15.0 | 135 | 1.1273 | 0.6007 | |
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| 0.9986 | 16.0 | 144 | 1.0976 | 0.6215 | |
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| 0.9289 | 17.0 | 153 | 1.0150 | 0.6528 | |
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| 0.9288 | 18.0 | 162 | 0.9629 | 0.6667 | |
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| 0.8092 | 19.0 | 171 | 0.9882 | 0.6528 | |
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| 0.7641 | 20.0 | 180 | 0.9357 | 0.6806 | |
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| 0.7641 | 21.0 | 189 | 0.9578 | 0.6840 | |
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| 0.7073 | 22.0 | 198 | 0.8655 | 0.6806 | |
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| 0.7277 | 23.0 | 207 | 1.0007 | 0.6632 | |
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| 0.6614 | 24.0 | 216 | 0.8399 | 0.7222 | |
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| 0.6571 | 25.0 | 225 | 0.8995 | 0.6875 | |
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| 0.6304 | 26.0 | 234 | 0.8523 | 0.7118 | |
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| 0.6298 | 27.0 | 243 | 0.8918 | 0.7049 | |
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| 0.5929 | 28.0 | 252 | 0.8510 | 0.7222 | |
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| 0.5915 | 29.0 | 261 | 0.8443 | 0.7257 | |
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| 0.5807 | 30.0 | 270 | 0.8536 | 0.7257 | |
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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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