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--- |
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license: apache-2.0 |
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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-base-EMOPIA |
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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-base-EMOPIA |
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This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.0286 |
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- Accuracy: 0.6200 |
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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: 1e-05 |
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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: 3 |
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- total_train_batch_size: 12 |
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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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- num_epochs: 15 |
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- mixed_precision_training: Native AMP |
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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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| 1.2694 | 0.98 | 41 | 1.1830 | 0.4800 | |
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| 1.0457 | 1.98 | 82 | 1.0959 | 0.4400 | |
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| 0.9201 | 2.98 | 123 | 0.9280 | 0.5600 | |
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| 0.8003 | 3.98 | 164 | 0.9346 | 0.7000 | |
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| 0.7616 | 4.98 | 205 | 0.9257 | 0.6600 | |
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| 0.6955 | 5.98 | 246 | 0.8411 | 0.7200 | |
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| 0.6743 | 6.98 | 287 | 0.9604 | 0.6200 | |
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| 0.5737 | 7.98 | 328 | 0.8471 | 0.7000 | |
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| 0.5269 | 8.98 | 369 | 1.0581 | 0.6000 | |
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| 0.4671 | 9.98 | 410 | 1.0365 | 0.6400 | |
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| 0.4227 | 10.98 | 451 | 1.0994 | 0.6000 | |
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| 0.3688 | 11.98 | 492 | 1.0964 | 0.5800 | |
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| 0.355 | 12.98 | 533 | 1.0586 | 0.5800 | |
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| 0.3232 | 13.98 | 574 | 1.0414 | 0.6000 | |
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| 0.3045 | 14.98 | 615 | 1.0286 | 0.6200 | |
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### Framework versions |
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- Transformers 4.18.0 |
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- Pytorch 1.10.1+cu102 |
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- Datasets 2.4.0 |
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- Tokenizers 0.12.1 |
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