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Finetuning-model-fr-covid-tweet-sentiment-classification
HLami/Finetuning-model-fr-covid-tweet-sentiment-classification
Finetuning-model-fr-covid-tweet-sentiment-classification is a text classification model from HLami. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- camembert
- Access
- Public
- Created
- Dec 1, 2023
- Updated
- Dec 1, 2023
- SHA
- 2b24744e
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Base models
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. -->
Finetuning-model-fr-covid-tweet-sentiment-classification
This model is a fine-tuned version of data354/camembert-fr-covid-tweet-sentiment-classification on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.7569
- Accuracy: 0.7633
- F1: 0.7633
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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| No log | 1.0 | 300 | 0.9091 | 0.7483 | 0.7483 |
| 0.2597 | 2.0 | 600 | 0.6695 | 0.7675 | 0.7675 |
| 0.2597 | 3.0 | 900 | 0.7569 | 0.7633 | 0.7633 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
- Task
- Text Classification
- Library
- transformers
- Type
- camembert
- License
- apache-2.0
- Created
- Dec 1, 2023
- Updated
- Dec 1, 2023