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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_bert-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_bert-base-on-IEMOCAP_2
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.3186
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- Accuracy: 0.7410
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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: 2e-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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- 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: 20
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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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| 1.3127 | 1.0 | 113 | 1.2620 | 0.4192 |
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| 0.957 | 2.0 | 226 | 0.9294 | 0.6095 |
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| 0.6409 | 3.0 | 339 | 0.8338 | 0.6969 |
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| 0.5966 | 4.0 | 452 | 0.8386 | 0.6958 |
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| 0.3725 | 5.0 | 565 | 0.8635 | 0.7035 |
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| 0.3556 | 6.0 | 678 | 0.9218 | 0.7069 |
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| 0.2466 | 7.0 | 791 | 0.9679 | 0.6914 |
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| 0.1737 | 8.0 | 904 | 1.1180 | 0.6869 |
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| 0.1694 | 9.0 | 1017 | 1.1068 | 0.6947 |
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| 0.1843 | 10.0 | 1130 | 1.1409 | 0.6903 |
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| 0.1747 | 11.0 | 1243 | 1.1143 | 0.7080 |
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| 0.1387 | 12.0 | 1356 | 1.2127 | 0.6991 |
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| 0.1524 | 13.0 | 1469 | 1.2309 | 0.7069 |
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| 0.1113 | 14.0 | 1582 | 1.2382 | 0.7113 |
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| 0.1278 | 15.0 | 1695 | 1.3048 | 0.7124 |
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| 0.1214 | 16.0 | 1808 | 1.3267 | 0.7146 |
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| 0.1965 | 17.0 | 1921 | 1.3726 | 0.7013 |
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| 0.1227 | 18.0 | 2034 | 1.3371 | 0.7168 |
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| 0.1014 | 19.0 | 2147 | 1.3508 | 0.7124 |
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| 0.1028 | 20.0 | 2260 | 1.3585 | 0.7080 |
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### Framework versions
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- Transformers 4.30.1
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- Pytorch 2.0.1+cu118
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- Datasets 2.12.0
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- Tokenizers 0.13.3
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