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multilingual-e5-large-instruct-edu-scorer-lr5e5-bs32

Text Classification
Transformers
Safetensors
xlm-roberta
Generated from Trainer
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  1. .gitattributes +1 -0
  2. README.md +126 -0
  3. all_results.json +11 -0
  4. config.json +34 -0
  5. final/config.json +32 -0
  6. final/model.safetensors +3 -0
  7. final/special_tokens_map.json +37 -0
  8. final/tokenizer.json +0 -0
  9. final/tokenizer_config.json +63 -0
  10. final/training_args.bin +3 -0
  11. final/vocab.txt +0 -0
  12. model.safetensors +3 -0
  13. special_tokens_map.json +51 -0
  14. test_results.json +11 -0
  15. tokenizer.json +3 -0
  16. tokenizer_config.json +56 -0
  17. training_args.bin +3 -0
  18. vocab.txt +0 -0
.gitattributes CHANGED
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README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: apache-2.0
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+ base_model: Snowflake/snowflake-arctic-embed-m
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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: snowflake-arctic-embed-m-edu-scorer-lr3e4-bs32
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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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+ # snowflake-arctic-embed-m-edu-scorer-lr3e4-bs32
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+
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+ This model is a fine-tuned version of [Snowflake/snowflake-arctic-embed-m](https://huggingface.co/Snowflake/snowflake-arctic-embed-m) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.5590
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+ - Precision: 0.4789
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+ - Recall: 0.2833
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+ - F1 Macro: 0.2779
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+ - Accuracy: 0.3073
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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: 0.0003
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+ - train_batch_size: 32
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+ - eval_batch_size: 32
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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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+ - lr_scheduler_warmup_ratio: 0.1
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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 | 3.1167 | 0.0587 | 0.1667 | 0.0869 | 0.3524 |
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+ | 0.994 | 0.3368 | 1000 | 0.9856 | 0.2966 | 0.2691 | 0.2391 | 0.397 |
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+ | 0.9708 | 0.6736 | 2000 | 0.9981 | 0.3297 | 0.2844 | 0.2609 | 0.4404 |
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+ | 1.0021 | 1.0104 | 3000 | 0.9604 | 0.3580 | 0.2772 | 0.2524 | 0.391 |
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+ | 0.9775 | 1.3473 | 4000 | 1.0404 | 0.3467 | 0.2686 | 0.2393 | 0.3408 |
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+ | 0.9321 | 1.6841 | 5000 | 0.9524 | 0.3051 | 0.2840 | 0.2591 | 0.4184 |
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+ | 0.9446 | 2.0209 | 6000 | 0.9473 | 0.3444 | 0.2819 | 0.2571 | 0.4018 |
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+ | 0.9997 | 2.3577 | 7000 | 0.9371 | 0.3497 | 0.2870 | 0.2653 | 0.4198 |
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+ | 0.9184 | 2.6945 | 8000 | 0.9295 | 0.3579 | 0.2989 | 0.2883 | 0.4292 |
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+ | 0.9196 | 3.0313 | 9000 | 0.9193 | 0.3422 | 0.2972 | 0.2794 | 0.446 |
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+ | 0.9115 | 3.3681 | 10000 | 0.9506 | 0.3245 | 0.2882 | 0.2697 | 0.4596 |
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+ | 0.8851 | 3.7050 | 11000 | 0.8964 | 0.3725 | 0.2954 | 0.2810 | 0.4382 |
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+ | 0.9021 | 4.0418 | 12000 | 0.8843 | 0.3722 | 0.3019 | 0.2890 | 0.4496 |
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+ | 0.8914 | 4.3786 | 13000 | 0.8831 | 0.3764 | 0.2950 | 0.2811 | 0.4266 |
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+ | 0.8962 | 4.7154 | 14000 | 0.8757 | 0.3609 | 0.3029 | 0.2864 | 0.4572 |
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+ | 0.8414 | 5.0522 | 15000 | 0.8788 | 0.3725 | 0.3079 | 0.2922 | 0.4678 |
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+ | 0.8621 | 5.3890 | 16000 | 0.8677 | 0.3684 | 0.3109 | 0.3012 | 0.4622 |
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+ | 0.8172 | 5.7258 | 17000 | 0.8725 | 0.3877 | 0.3021 | 0.2884 | 0.4654 |
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+ | 0.8282 | 6.0626 | 18000 | 0.8833 | 0.3651 | 0.3051 | 0.2951 | 0.4702 |
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+ | 0.8652 | 6.3995 | 19000 | 0.8535 | 0.3712 | 0.3200 | 0.3126 | 0.4604 |
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+ | 0.8123 | 6.7363 | 20000 | 0.8529 | 0.3664 | 0.3075 | 0.2931 | 0.4434 |
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+ | 0.8402 | 7.0731 | 21000 | 0.8461 | 0.3816 | 0.3099 | 0.2969 | 0.466 |
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+ | 0.8082 | 7.4099 | 22000 | 0.8515 | 0.3681 | 0.3193 | 0.3118 | 0.4636 |
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+ | 0.7828 | 8.0835 | 24000 | 0.8476 | 0.3936 | 0.3187 | 0.3114 | 0.4756 |
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+ | 0.806 | 8.4203 | 25000 | 0.8364 | 0.3875 | 0.3168 | 0.3075 | 0.4644 |
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+ | 0.8356 | 8.7572 | 26000 | 0.8511 | 0.3869 | 0.3282 | 0.3223 | 0.4538 |
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+ | 0.8418 | 9.0940 | 27000 | 0.8398 | 0.3679 | 0.3127 | 0.2988 | 0.4676 |
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+ | 0.8087 | 9.4308 | 28000 | 0.8384 | 0.3795 | 0.3188 | 0.3101 | 0.4516 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.53.2
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+ - Pytorch 2.7.1+cu126
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+ - Datasets 4.0.0
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+ - Tokenizers 0.21.2
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