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End of training

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README.md ADDED
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+ ---
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+ base_model: camembert/camembert-base-ccnet
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: camembert_ccnet_classification_tools_NEFTune_fr_lr1e-3_V2
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+ results: []
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+ ---
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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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+
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+ # camembert_ccnet_classification_tools_NEFTune_fr_lr1e-3_V2
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+
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+ This model is a fine-tuned version of [camembert/camembert-base-ccnet](https://huggingface.co/camembert/camembert-base-ccnet) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 2.0965
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+ - Accuracy: 0.1042
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+ - Learning Rate: 0.0008
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 0.001
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+ - train_batch_size: 24
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+ - eval_batch_size: 192
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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: 60
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | Rate |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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+ | 2.1119 | 1.0 | 15 | 2.1246 | 0.1042 | 0.0010 |
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+ | 2.0909 | 2.0 | 30 | 2.1521 | 0.0938 | 0.0010 |
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+ | 2.1043 | 3.0 | 45 | 2.0959 | 0.0938 | 0.0009 |
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+ | 2.0866 | 4.0 | 60 | 2.1143 | 0.0938 | 0.0009 |
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+ | 2.0746 | 5.0 | 75 | 2.1063 | 0.1354 | 0.0009 |
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+ | 2.0753 | 6.0 | 90 | 2.1266 | 0.0938 | 0.0009 |
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+ | 2.0793 | 7.0 | 105 | 2.1177 | 0.1146 | 0.0009 |
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+ | 2.0844 | 8.0 | 120 | 2.0959 | 0.1354 | 0.0009 |
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+ | 2.0855 | 9.0 | 135 | 2.1072 | 0.0938 | 0.0008 |
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+ | 2.0805 | 10.0 | 150 | 2.1128 | 0.0938 | 0.0008 |
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+ | 2.079 | 11.0 | 165 | 2.1027 | 0.1354 | 0.0008 |
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+ | 2.0855 | 12.0 | 180 | 2.1164 | 0.0938 | 0.0008 |
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+ | 2.0745 | 13.0 | 195 | 2.0965 | 0.1042 | 0.0008 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.34.0
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+ - Pytorch 2.0.1+cu117
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+ - Datasets 2.14.5
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+ - Tokenizers 0.14.1
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