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--- |
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base_model: cardiffnlp/twitter-roberta-base-emotion |
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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_roberta-base-on-IEMOCAP_4 |
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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_roberta-base-on-IEMOCAP_4 |
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This model is a fine-tuned version of [cardiffnlp/twitter-roberta-base-emotion](https://huggingface.co/cardiffnlp/twitter-roberta-base-emotion) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.5143 |
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- Accuracy: 0.6867 |
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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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- 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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| 0.8876 | 1.0 | 113 | 0.9530 | 0.6341 | |
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| 0.7153 | 2.0 | 226 | 0.8473 | 0.6807 | |
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| 0.5127 | 3.0 | 339 | 0.8841 | 0.6907 | |
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| 0.3844 | 4.0 | 452 | 0.9751 | 0.7062 | |
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| 0.3104 | 5.0 | 565 | 0.9363 | 0.7029 | |
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| 0.2374 | 6.0 | 678 | 1.1047 | 0.6896 | |
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| 0.2128 | 7.0 | 791 | 1.1239 | 0.7040 | |
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| 0.2104 | 8.0 | 904 | 1.1717 | 0.7129 | |
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| 0.1896 | 9.0 | 1017 | 1.1580 | 0.6973 | |
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| 0.1211 | 10.0 | 1130 | 1.2320 | 0.7029 | |
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| 0.1737 | 11.0 | 1243 | 1.3389 | 0.6973 | |
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| 0.1022 | 12.0 | 1356 | 1.3537 | 0.7062 | |
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| 0.0934 | 13.0 | 1469 | 1.3742 | 0.7140 | |
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| 0.0987 | 14.0 | 1582 | 1.4039 | 0.7151 | |
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| 0.1065 | 15.0 | 1695 | 1.4150 | 0.7173 | |
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### Framework versions |
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- Transformers 4.34.0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.14.1 |
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