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feel_it_finetuned_pro_emit_multilabel2
lupobricco/feel_it_finetuned_pro_emit_multilabel2
feel_it_finetuned_pro_emit_multilabel2 is a text classification model from lupobricco. Use it when you need a label for a piece of text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- camembert
- Access
- Public
- Created
- Apr 2, 2024
- Updated
- Apr 2, 2024
- SHA
- 604fbc62
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Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
feel_it_finetuned_pro_emit_multilabel2
This model is a fine-tuned version of MilaNLProc/feel-it-italian-emotion on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2731
- F1: 0.4953
- Roc Auc: 0.6999
- Accuracy: 0.3239
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
|---|---|---|---|---|---|---|
| No log | 1.0 | 444 | 0.3172 | 0.2675 | 0.5782 | 0.1527 |
| 0.3614 | 2.0 | 888 | 0.2856 | 0.4172 | 0.6463 | 0.2794 |
| 0.2837 | 3.0 | 1332 | 0.2760 | 0.4727 | 0.6793 | 0.3076 |
| 0.2408 | 4.0 | 1776 | 0.2732 | 0.4940 | 0.6953 | 0.3301 |
| 0.217 | 5.0 | 2220 | 0.2731 | 0.4953 | 0.6999 | 0.3239 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.0.0+cu118
- Datasets 2.18.0
- Tokenizers 0.15.2
- Task
- Text Classification
- Library
- transformers
- Type
- camembert
- Created
- Apr 2, 2024
- Updated
- Apr 2, 2024