End of training
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README.md
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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.
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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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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 | 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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model.safetensors
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