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finerweb-binary-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-binary-xlm-roberta-base-lr5e-05-20250411_122038
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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-binary-xlm-roberta-base-lr5e-05-20250411_122038
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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: 0.1567
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+ - Precision: 0.8363
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+ - Recall: 0.8275
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+ - F1 Macro: 0.8307
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+ - Accuracy: 0.8358
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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 | 0.4902 | 0.2156 | 0.5 | 0.3013 | 0.4311 |
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+ | 0.113 | 0.7812 | 1000 | 0.1096 | 0.8549 | 0.8348 | 0.8405 | 0.8472 |
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+ | 0.0936 | 1.5625 | 2000 | 0.1076 | 0.8531 | 0.8457 | 0.8486 | 0.8528 |
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+ | 0.0614 | 2.3438 | 3000 | 0.1205 | 0.8425 | 0.8381 | 0.8400 | 0.8439 |
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+ | 0.0431 | 3.125 | 4000 | 0.1294 | 0.8341 | 0.8392 | 0.8355 | 0.8371 |
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+ | 0.0476 | 3.9062 | 5000 | 0.1448 | 0.8453 | 0.8226 | 0.8285 | 0.8364 |
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+ | 0.0332 | 4.6875 | 6000 | 0.1394 | 0.8403 | 0.8261 | 0.8306 | 0.8368 |
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+ | 0.0258 | 5.4688 | 7000 | 0.1402 | 0.8380 | 0.8331 | 0.8351 | 0.8393 |
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+ | 0.0234 | 6.25 | 8000 | 0.1382 | 0.8411 | 0.8285 | 0.8326 | 0.8384 |
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+ | 0.019 | 7.0312 | 9000 | 0.1398 | 0.8381 | 0.8295 | 0.8326 | 0.8377 |
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+ | 0.0172 | 7.8125 | 10000 | 0.1569 | 0.8344 | 0.8134 | 0.8190 | 0.8270 |
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+ | 0.016 | 8.5938 | 11000 | 0.1440 | 0.8399 | 0.8286 | 0.8324 | 0.8380 |
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+ | 0.0127 | 9.375 | 12000 | 0.1500 | 0.8394 | 0.8341 | 0.8363 | 0.8405 |
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+ | 0.0102 | 10.1562 | 13000 | 0.1497 | 0.8331 | 0.8330 | 0.8331 | 0.8362 |
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+ | 0.0121 | 10.9375 | 14000 | 0.1506 | 0.8355 | 0.8210 | 0.8255 | 0.8320 |
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+ | 0.008 | 11.7188 | 15000 | 0.1491 | 0.8410 | 0.8302 | 0.8339 | 0.8393 |
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+ | 0.009 | 12.5 | 16000 | 0.1456 | 0.8384 | 0.8350 | 0.8364 | 0.8403 |
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+ | 0.0053 | 13.2812 | 17000 | 0.1542 | 0.8377 | 0.8277 | 0.8312 | 0.8366 |
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+ | 0.0062 | 14.0625 | 18000 | 0.1514 | 0.8347 | 0.8318 | 0.8331 | 0.8369 |
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+ | 0.0034 | 14.8438 | 19000 | 0.1549 | 0.8325 | 0.8335 | 0.8330 | 0.8359 |
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+ | 0.0045 | 15.625 | 20000 | 0.1530 | 0.8343 | 0.8309 | 0.8324 | 0.8364 |
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+ | 0.0036 | 16.4062 | 21000 | 0.1555 | 0.8312 | 0.8315 | 0.8314 | 0.8345 |
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+ | 0.001 | 17.1875 | 22000 | 0.1573 | 0.8329 | 0.8308 | 0.8318 | 0.8355 |
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+ | 0.0029 | 17.9688 | 23000 | 0.1558 | 0.8334 | 0.8309 | 0.8320 | 0.8358 |
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+ | 0.0018 | 18.75 | 24000 | 0.1543 | 0.8376 | 0.8357 | 0.8366 | 0.8401 |
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+ | 0.0018 | 19.5312 | 25000 | 0.1567 | 0.8363 | 0.8275 | 0.8307 | 0.8358 |
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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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+ "hidden_size": 768,
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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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+ "pad_token_id": 1,
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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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