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--- |
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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-v7 |
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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-v7 |
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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: 0.8320 |
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- Accuracy: 0.7986 |
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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: 5 |
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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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| 0.2518 | 0.15 | 25 | 1.0813 | 0.7222 | |
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| 0.4377 | 0.31 | 50 | 1.3678 | 0.6389 | |
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| 0.471 | 0.46 | 75 | 1.2841 | 0.6458 | |
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| 0.6906 | 0.62 | 100 | 1.0845 | 0.6736 | |
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| 0.8409 | 0.77 | 125 | 0.9987 | 0.7222 | |
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| 0.5912 | 0.93 | 150 | 0.9029 | 0.7292 | |
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| 0.6029 | 1.08 | 175 | 1.0862 | 0.6597 | |
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| 0.4525 | 1.23 | 200 | 1.0455 | 0.6806 | |
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| 0.4263 | 1.39 | 225 | 1.4209 | 0.6389 | |
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| 0.4866 | 1.54 | 250 | 1.0648 | 0.7222 | |
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| 0.3619 | 1.7 | 275 | 0.9949 | 0.7083 | |
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| 0.7256 | 1.85 | 300 | 1.1846 | 0.6875 | |
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| 0.3964 | 2.01 | 325 | 0.9130 | 0.7222 | |
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| 0.2853 | 2.16 | 350 | 1.0839 | 0.7292 | |
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| 0.3022 | 2.31 | 375 | 0.7729 | 0.7847 | |
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| 0.3631 | 2.47 | 400 | 1.2372 | 0.7153 | |
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| 0.3029 | 2.62 | 425 | 0.9880 | 0.7778 | |
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| 0.2665 | 2.78 | 450 | 1.1243 | 0.7569 | |
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| 0.2743 | 2.93 | 475 | 0.8395 | 0.7778 | |
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| 0.1787 | 3.09 | 500 | 0.8320 | 0.7986 | |
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| 0.1533 | 3.24 | 525 | 0.8909 | 0.7778 | |
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| 0.1636 | 3.4 | 550 | 1.1212 | 0.7569 | |
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| 0.1677 | 3.55 | 575 | 0.9527 | 0.7986 | |
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| 0.1166 | 3.7 | 600 | 0.9082 | 0.8056 | |
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| 0.1923 | 3.86 | 625 | 1.1074 | 0.75 | |
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| 0.108 | 4.01 | 650 | 1.0360 | 0.7847 | |
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| 0.1023 | 4.17 | 675 | 1.0964 | 0.7708 | |
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| 0.1122 | 4.32 | 700 | 1.2101 | 0.7569 | |
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| 0.1501 | 4.48 | 725 | 0.9138 | 0.8125 | |
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| 0.098 | 4.63 | 750 | 0.8422 | 0.8194 | |
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| 0.0585 | 4.78 | 775 | 1.0018 | 0.7917 | |
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| 0.1135 | 4.94 | 800 | 1.0409 | 0.7847 | |
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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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