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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-base |
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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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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: wav2vec2transformerEMR3 |
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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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# wav2vec2transformerEMR3 |
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This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6589 |
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- Accuracy: 0.7916 |
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- Precision: 0.7918 |
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- Recall: 0.7916 |
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- F1: 0.7896 |
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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: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 32 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 500 |
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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 | Precision | Recall | F1 | |
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|:-------------:|:-------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
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| 1.4706 | 1.6420 | 500 | 1.4207 | 0.5409 | 0.5559 | 0.5409 | 0.5180 | |
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| 0.953 | 3.2841 | 1000 | 0.9292 | 0.7275 | 0.7438 | 0.7275 | 0.7233 | |
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| 0.7575 | 4.9261 | 1500 | 0.7618 | 0.7616 | 0.7686 | 0.7616 | 0.7610 | |
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| 0.6084 | 6.5681 | 2000 | 0.7485 | 0.7559 | 0.7658 | 0.7559 | 0.7524 | |
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| 0.5221 | 8.2102 | 2500 | 0.6990 | 0.7711 | 0.7767 | 0.7711 | 0.7691 | |
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| 0.431 | 9.8522 | 3000 | 0.6967 | 0.7752 | 0.7796 | 0.7752 | 0.7719 | |
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| 0.3814 | 11.4943 | 3500 | 0.6523 | 0.7867 | 0.7875 | 0.7867 | 0.7856 | |
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| 0.3461 | 13.1363 | 4000 | 0.6589 | 0.7916 | 0.7918 | 0.7916 | 0.7896 | |
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| 0.3405 | 14.7783 | 4500 | 0.6703 | 0.7867 | 0.7878 | 0.7867 | 0.7847 | |
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### Framework versions |
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- Transformers 4.46.2 |
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- Pytorch 2.5.1+cu121 |
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- Tokenizers 0.20.3 |
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