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--- |
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license: mit |
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base_model: camembert-base |
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tags: |
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- generated_from_trainer |
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datasets: |
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- tweet_sentiment_multilingual |
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metrics: |
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- accuracy |
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model-index: |
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- name: camembert_model |
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results: |
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- task: |
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name: Text Classification |
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type: text-classification |
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dataset: |
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name: tweet_sentiment_multilingual |
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type: tweet_sentiment_multilingual |
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config: french |
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split: validation |
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args: french |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.7654320987654321 |
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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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# camembert_model |
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This model is a fine-tuned version of [camembert-base](https://huggingface.co/camembert-base) on the tweet_sentiment_multilingual dataset (French portion of it) . |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7877 |
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- Accuracy: 0.7654 |
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## Model description |
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A sentiment Classifier for the french language |
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classifies french text to positive, negative or neutral. |
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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 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| No log | 1.0 | 115 | 0.8510 | 0.6265 | |
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| No log | 2.0 | 230 | 0.7627 | 0.7130 | |
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| No log | 3.0 | 345 | 0.6966 | 0.7160 | |
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| No log | 4.0 | 460 | 0.6862 | 0.7438 | |
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| 0.7126 | 5.0 | 575 | 0.6637 | 0.75 | |
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| 0.7126 | 6.0 | 690 | 0.7121 | 0.7654 | |
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| 0.7126 | 7.0 | 805 | 0.7641 | 0.7438 | |
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| 0.7126 | 8.0 | 920 | 0.7662 | 0.7654 | |
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| 0.2932 | 9.0 | 1035 | 0.7765 | 0.7747 | |
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| 0.2932 | 10.0 | 1150 | 0.7877 | 0.7654 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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