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--- |
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base_model: lupobricco/feel_it_finetuned_pro_emit_multilabel2 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- f1 |
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- accuracy |
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model-index: |
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- name: multilabel_emotion_classification_finetuned_multimodal |
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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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# multilabel_emotion_classification_finetuned_multimodal |
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This model is a fine-tuned version of [lupobricco/feel_it_finetuned_pro_emit_multilabel2](https://huggingface.co/lupobricco/feel_it_finetuned_pro_emit_multilabel2) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2439 |
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- F1: 0.5642 |
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- Roc Auc: 0.7425 |
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- Accuracy: 0.4087 |
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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: 16 |
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- eval_batch_size: 16 |
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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: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:| |
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| No log | 1.0 | 22 | 0.2472 | 0.4520 | 0.6658 | 0.3391 | |
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| No log | 2.0 | 44 | 0.2445 | 0.4927 | 0.6909 | 0.3507 | |
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| No log | 3.0 | 66 | 0.2439 | 0.5 | 0.6941 | 0.3594 | |
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| No log | 4.0 | 88 | 0.2436 | 0.5297 | 0.7209 | 0.3652 | |
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| No log | 5.0 | 110 | 0.2424 | 0.5400 | 0.7313 | 0.3710 | |
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| No log | 6.0 | 132 | 0.2409 | 0.5450 | 0.7276 | 0.3768 | |
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| No log | 7.0 | 154 | 0.2432 | 0.5286 | 0.7191 | 0.3652 | |
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| No log | 8.0 | 176 | 0.2433 | 0.5501 | 0.7336 | 0.3942 | |
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| No log | 9.0 | 198 | 0.2439 | 0.5642 | 0.7425 | 0.4087 | |
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| No log | 10.0 | 220 | 0.2434 | 0.5594 | 0.7406 | 0.4029 | |
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### Framework versions |
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- Transformers 4.39.3 |
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- Pytorch 1.11.0 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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