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---
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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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- f1
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model-index:
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- name: wavlm-large-finetuned-iemocap
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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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# wavlm-large-finetuned-iemocap
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This model is a fine-tuned version of [microsoft/wavlm-large](https://huggingface.co/microsoft/wavlm-large) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.1588
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- Accuracy: 0.4811
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- F1: 0.4602
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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: 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: 10
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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| 1.3733 | 0.98 | 25 | 1.3723 | 0.2502 | 0.1002 |
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| 1.2784 | 1.98 | 50 | 1.3130 | 0.3307 | 0.2503 |
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| 1.2228 | 2.98 | 75 | 1.2485 | 0.3899 | 0.3398 |
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| 1.1588 | 3.98 | 100 | 1.2129 | 0.4646 | 0.4650 |
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| 1.1116 | 4.98 | 125 | 1.1941 | 0.4753 | 0.4655 |
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| 1.1212 | 5.98 | 150 | 1.1688 | 0.4762 | 0.4639 |
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| 1.0919 | 6.98 | 175 | 1.1574 | 0.4850 | 0.4710 |
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| 1.0749 | 7.98 | 200 | 1.1612 | 0.4840 | 0.4639 |
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| 1.0943 | 8.98 | 225 | 1.1586 | 0.4888 | 0.4677 |
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| 1.0746 | 9.98 | 250 | 1.1588 | 0.4811 | 0.4602 |
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### Framework versions
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- Transformers 4.26.1
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- Pytorch 1.13.1+cu116
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- Datasets 2.9.0
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- Tokenizers 0.13.2
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