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--- |
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license: mit |
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tags: |
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- generated_from_trainer |
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metrics: |
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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: distilcamembert-cae-all |
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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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Gustave Cortal, Alain Finkel, Patrick Paroubek, Lina Ye. May 2023. *Emotion Recognition based on Psychological Components in Guided Narratives for Emotion Regulation*. |
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In Proceedings of the 7th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature, pages 72–81, Dubrovnik, Croatia. Association for Computational Linguistics. |
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[paper](https://aclanthology.org/2023.latechclfl-1.8/), [slides](https://gustavecortal.com/data/Emotion_Recognition_based_on_Psychological_Components_slides.pdf), [video](https://underline.io/lecture/71953-emotion-recognition-based-on-psychological-components-in-guided-narratives-for-emotion-regulation) |
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# distilcamembert-cae-all |
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This model is a fine-tuned version of [cmarkea/distilcamembert-base](https://huggingface.co/cmarkea/distilcamembert-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6016 |
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- Precision: 0.8510 |
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- Recall: 0.8481 |
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- F1: 0.8471 |
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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: 5e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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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: 5.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:| |
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| 1.18 | 1.0 | 40 | 0.9901 | 0.6418 | 0.4557 | 0.2991 | |
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| 0.8718 | 2.0 | 80 | 0.6938 | 0.7667 | 0.7468 | 0.7196 | |
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| 0.4656 | 3.0 | 120 | 0.6928 | 0.8364 | 0.8354 | 0.8353 | |
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| 0.2418 | 4.0 | 160 | 0.6008 | 0.8276 | 0.8228 | 0.8228 | |
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| 0.1285 | 5.0 | 200 | 0.6016 | 0.8510 | 0.8481 | 0.8471 | |
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### Framework versions |
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- Transformers 4.24.0 |
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- Pytorch 1.12.1+cu113 |
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- Datasets 2.7.1 |
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- Tokenizers 0.13.2 |
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