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finerweb-multilabel-classifier-xlmr-4o

Text Classification
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Safetensors
xlm-roberta
Generated from Trainer
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  1. README.md +91 -0
  2. final/config.json +35 -0
  3. final/model.safetensors +3 -0
  4. final/sentencepiece.bpe.model +3 -0
  5. final/special_tokens_map.json +15 -0
  6. final/tokenizer.json +3 -0
  7. final/tokenizer_config.json +55 -0
  8. final/training_args.bin +3 -0
  9. model.safetensors +1 -1
README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: mit
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+ base_model: FacebookAI/xlm-roberta-base
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - precision
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+ - recall
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+ - accuracy
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+ model-index:
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+ - name: openai-fineweb-edu-scorer-xlm-multilabel-xlm-roberta-base-lr5e-05-20250411_122059
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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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+ # openai-fineweb-edu-scorer-xlm-multilabel-xlm-roberta-base-lr5e-05-20250411_122059
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+
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+ This model is a fine-tuned version of [FacebookAI/xlm-roberta-base](https://huggingface.co/FacebookAI/xlm-roberta-base) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.3645
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+ - Precision: 0.5930
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+ - Recall: 0.4813
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+ - F1 Macro: 0.5091
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+ - Accuracy: 0.6488
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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: 5e-05
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+ - train_batch_size: 64
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+ - eval_batch_size: 128
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+ - seed: 0
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+ - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: linear
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+ - num_epochs: 20
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 Macro | Accuracy |
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+ |:-------------:|:-------:|:-----:|:---------------:|:---------:|:------:|:--------:|:--------:|
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+ | No log | 0 | 0 | 8.1215 | 0.0002 | 0.2 | 0.0004 | 0.0010 |
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+ | 0.2936 | 0.7812 | 1000 | 0.2877 | 0.5095 | 0.4544 | 0.4485 | 0.6647 |
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+ | 0.2516 | 1.5625 | 2000 | 0.3197 | 0.5299 | 0.3886 | 0.4136 | 0.6293 |
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+ | 0.1737 | 2.3438 | 3000 | 0.2922 | 0.5089 | 0.4296 | 0.4518 | 0.6516 |
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+ | 0.0996 | 3.125 | 4000 | 0.3233 | 0.5012 | 0.4379 | 0.4585 | 0.6369 |
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+ | 0.1051 | 3.9062 | 5000 | 0.3108 | 0.5042 | 0.4401 | 0.4609 | 0.6496 |
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+ | 0.0601 | 4.6875 | 6000 | 0.3501 | 0.4840 | 0.4501 | 0.4614 | 0.6411 |
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+ | 0.0588 | 5.4688 | 7000 | 0.3554 | 0.4758 | 0.4585 | 0.4658 | 0.6327 |
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+ | 0.0385 | 6.25 | 8000 | 0.3527 | 0.4853 | 0.4518 | 0.4647 | 0.6331 |
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+ | 0.0312 | 7.0312 | 9000 | 0.3475 | 0.4912 | 0.4580 | 0.4714 | 0.6415 |
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+ | 0.0314 | 7.8125 | 10000 | 0.3442 | 0.4983 | 0.4557 | 0.4679 | 0.6551 |
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+ | 0.0211 | 8.5938 | 11000 | 0.3543 | 0.4823 | 0.4740 | 0.4769 | 0.6449 |
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+ | 0.0193 | 9.375 | 12000 | 0.3585 | 0.4816 | 0.4621 | 0.4697 | 0.6438 |
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+ | 0.0208 | 10.1562 | 13000 | 0.3730 | 0.4825 | 0.4588 | 0.4659 | 0.6207 |
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+ | 0.0203 | 10.9375 | 14000 | 0.3578 | 0.4903 | 0.4748 | 0.4818 | 0.6468 |
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+ | 0.0154 | 11.7188 | 15000 | 0.3513 | 0.4994 | 0.4591 | 0.4744 | 0.6557 |
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+ | 0.0126 | 12.5 | 16000 | 0.3623 | 0.4920 | 0.4488 | 0.4649 | 0.6460 |
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+ | 0.0087 | 13.2812 | 17000 | 0.3632 | 0.4940 | 0.4512 | 0.4675 | 0.6449 |
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+ | 0.0091 | 14.0625 | 18000 | 0.3518 | 0.6976 | 0.4793 | 0.5121 | 0.6533 |
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+ | 0.009 | 14.8438 | 19000 | 0.3569 | 0.5918 | 0.4886 | 0.5128 | 0.6527 |
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+ | 0.0056 | 15.625 | 20000 | 0.3672 | 0.5532 | 0.4882 | 0.5081 | 0.6457 |
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+ | 0.0045 | 16.4062 | 21000 | 0.3655 | 0.5391 | 0.4870 | 0.5060 | 0.6460 |
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+ | 0.0035 | 17.1875 | 22000 | 0.3646 | 0.4955 | 0.4634 | 0.4765 | 0.6489 |
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+ | 0.0032 | 17.9688 | 23000 | 0.3631 | 0.6942 | 0.4841 | 0.5150 | 0.6503 |
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+ | 0.0035 | 18.75 | 24000 | 0.3625 | 0.5986 | 0.4805 | 0.5103 | 0.6504 |
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+ | 0.0019 | 19.5312 | 25000 | 0.3645 | 0.5930 | 0.4813 | 0.5091 | 0.6488 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.49.0
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+ - Pytorch 2.6.0+cu124
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+ - Datasets 3.3.2
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+ - Tokenizers 0.21.1
final/config.json ADDED
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+ {
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+ "_name_or_path": "FacebookAI/xlm-roberta-base",
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+ "architectures": [
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+ "XLMRobertaForSequenceClassification"
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+ "layer_norm_eps": 1e-05,
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+ "max_position_embeddings": 514,
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+ "model_type": "xlm-roberta",
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+ "num_attention_heads": 12,
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+ "num_hidden_layers": 12,
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+ "output_past": true,
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+ "position_embedding_type": "absolute",
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+ "problem_type": "regression",
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.49.0",
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+ "type_vocab_size": 1,
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+ "use_cache": true,
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+ "vocab_size": 250002
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+ }
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