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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: finetuned_wav2vec2.0-base-on-IEMOCAP_2 |
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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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# finetuned_wav2vec2.0-base-on-IEMOCAP_2 |
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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: 1.1569 |
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- Accuracy: 0.7390 |
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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: 3e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 32 |
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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: 15 |
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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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| 1.1881 | 0.99 | 112 | 1.2005 | 0.4768 | |
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| 1.0121 | 2.0 | 225 | 1.0271 | 0.5619 | |
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| 0.8569 | 3.0 | 338 | 0.9382 | 0.6018 | |
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| 0.8679 | 4.0 | 451 | 0.8015 | 0.6947 | |
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| 0.5643 | 4.99 | 563 | 0.7752 | 0.7046 | |
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| 0.4579 | 6.0 | 676 | 0.7699 | 0.7400 | |
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| 0.3993 | 7.0 | 789 | 0.8323 | 0.7102 | |
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| 0.319 | 8.0 | 902 | 0.7763 | 0.7400 | |
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| 0.1876 | 8.99 | 1014 | 0.8912 | 0.7334 | |
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| 0.1888 | 10.0 | 1127 | 0.8836 | 0.7312 | |
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| 0.1526 | 11.0 | 1240 | 1.0474 | 0.7290 | |
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| 0.0451 | 12.0 | 1353 | 1.0455 | 0.7434 | |
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| 0.1281 | 12.99 | 1465 | 1.1207 | 0.7412 | |
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| 0.0363 | 14.0 | 1578 | 1.1232 | 0.7445 | |
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| 0.0512 | 14.9 | 1680 | 1.1217 | 0.7412 | |
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### Framework versions |
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- Transformers 4.29.2 |
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- Pytorch 2.0.0 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
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