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camembert-pcg-annotation-full

Text Classification
Transformers
Safetensors
camembert
Generated from Trainer
text-embeddings-inference
Model card Files
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Add camembert PCG model

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  1. README.md +82 -0
  2. final/classification_report.json +1701 -0
  3. final/config.json +760 -0
  4. final/label_registry.json +734 -0
  5. final/model.safetensors +3 -0
  6. final/tokenizer.json +0 -0
  7. final/tokenizer_config.json +19 -0
  8. final/training_metadata.json +775 -0
  9. model.safetensors +1 -1
README.md ADDED
@@ -0,0 +1,82 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ library_name: transformers
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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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+ metrics:
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+ - accuracy
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+ - precision
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+ - recall
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+ model-index:
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+ - name: camembert-pcg-annotation-full
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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-pcg-annotation-full
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+
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+ This model is a fine-tuned version of [camembert-base](https://huggingface.co/camembert-base) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 5.8545
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+ - Accuracy: 0.0190
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+ - Top3 Accuracy: 0.0258
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+ - Top5 Accuracy: 0.0426
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+ - Precision: 0.0004
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+ - Recall: 0.0190
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+ - F1 Weighted: 0.0007
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+ - F1 Macro: 0.0001
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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: 2e-05
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+ - train_batch_size: 32
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+ - eval_batch_size: 32
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+ - seed: 42
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+ - gradient_accumulation_steps: 2
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+ - total_train_batch_size: 64
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+ - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: cosine
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+ - lr_scheduler_warmup_steps: 0.1
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+ - num_epochs: 5
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+ - mixed_precision_training: Native AMP
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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 | Top3 Accuracy | Top5 Accuracy | Precision | Recall | F1 Weighted | F1 Macro |
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+ |:-------------:|:------:|:----:|:---------------:|:--------:|:-------------:|:-------------:|:---------:|:------:|:-----------:|:--------:|
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+ | 11.7871 | 0.0035 | 100 | 5.8966 | 0.0009 | 0.0185 | 0.0199 | 0.0001 | 0.0009 | 0.0002 | 0.0000 |
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+ | 11.7889 | 0.0070 | 200 | 5.8956 | 0.0012 | 0.0189 | 0.0202 | 0.0001 | 0.0012 | 0.0003 | 0.0000 |
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+ | 11.7890 | 0.0106 | 300 | 5.8932 | 0.0027 | 0.0192 | 0.0213 | 0.0002 | 0.0027 | 0.0004 | 0.0001 |
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+ | 11.7868 | 0.0141 | 400 | 5.8905 | 0.0052 | 0.0194 | 0.0238 | 0.0003 | 0.0052 | 0.0005 | 0.0001 |
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+ | 11.7813 | 0.0176 | 500 | 5.8868 | 0.0100 | 0.0201 | 0.0248 | 0.0006 | 0.0100 | 0.0007 | 0.0002 |
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+ | 11.7618 | 0.0211 | 600 | 5.8820 | 0.0167 | 0.0204 | 0.0247 | 0.0004 | 0.0167 | 0.0007 | 0.0001 |
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+ | 11.7506 | 0.0246 | 700 | 5.8762 | 0.0184 | 0.0221 | 0.0274 | 0.0004 | 0.0184 | 0.0007 | 0.0002 |
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+ | 11.7522 | 0.0281 | 800 | 5.8695 | 0.0190 | 0.0225 | 0.0321 | 0.0004 | 0.0190 | 0.0008 | 0.0002 |
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+ | 11.7451 | 0.0317 | 900 | 5.8624 | 0.0190 | 0.0234 | 0.0356 | 0.0004 | 0.0190 | 0.0007 | 0.0001 |
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+ | 11.7221 | 0.0352 | 1000 | 5.8545 | 0.0190 | 0.0258 | 0.0426 | 0.0004 | 0.0190 | 0.0007 | 0.0001 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 5.2.0
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+ - Pytorch 2.10.0+cu128
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+ - Datasets 4.5.0
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+ - Tokenizers 0.22.2
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