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README.md
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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_5
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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_5
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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: 1.3146
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- Accuracy: 0.6624
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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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| 1.3037 | 1.0 | 108 | 1.2852 | 0.4349 |
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| 1.0277 | 2.0 | 216 | 0.9733 | 0.5942 |
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| 0.7985 | 3.0 | 324 | 0.8110 | 0.6895 |
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| 0.5244 | 4.0 | 432 | 0.7911 | 0.6919 |
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| 0.3289 | 5.0 | 540 | 0.8518 | 0.7012 |
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| 0.3281 | 6.0 | 648 | 0.9236 | 0.6884 |
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| 0.2689 | 7.0 | 756 | 0.9498 | 0.7058 |
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| 0.2162 | 8.0 | 864 | 1.0157 | 0.7023 |
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| 0.1811 | 9.0 | 972 | 1.0196 | 0.7151 |
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| 0.2283 | 10.0 | 1080 | 1.0987 | 0.7209 |
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| 0.1449 | 11.0 | 1188 | 1.1462 | 0.7186 |
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| 0.1614 | 12.0 | 1296 | 1.1972 | 0.7116 |
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| 0.1589 | 13.0 | 1404 | 1.2174 | 0.7163 |
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| 0.1314 | 14.0 | 1512 | 1.2388 | 0.7116 |
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| 0.1587 | 15.0 | 1620 | 1.2722 | 0.7186 |
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| 0.0928 | 16.0 | 1728 | 1.3090 | 0.7186 |
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| 0.1394 | 17.0 | 1836 | 1.3286 | 0.7174 |
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| 0.0958 | 18.0 | 1944 | 1.3321 | 0.7209 |
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| 0.0862 | 19.0 | 2052 | 1.3439 | 0.7128 |
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| 0.1041 | 20.0 | 2160 | 1.3473 | 0.7151 |
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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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