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stack-edu-classifier-swift

Text Classification
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  1. README.md +173 -0
  2. final/config.json +32 -0
  3. final/merges.txt +0 -0
  4. final/model.safetensors +3 -0
  5. final/special_tokens_map.json +45 -0
  6. final/tokenizer.json +0 -0
  7. final/tokenizer_config.json +186 -0
  8. final/training_args.bin +3 -0
  9. final/vocab.json +0 -0
  10. model.safetensors +1 -1
README.md ADDED
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+ ---
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+ base_model: bigcode/starencoder
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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: classifier-llama3-swift-500k
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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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+ # classifier-llama3-swift-500k
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+
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+ This model is a fine-tuned version of [bigcode/starencoder](https://huggingface.co/bigcode/starencoder) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.3403
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+ - Precision: 0.6596
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+ - Recall: 0.3962
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+ - F1 Macro: 0.4436
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+ - Accuracy: 0.6112
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+ - F1 Binary Minimum3: 0.7282
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+ - F1 Binary Minimum2: 0.9673
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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: 0.0001
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+ - train_batch_size: 16
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+ - eval_batch_size: 256
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+ - seed: 0
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+ - distributed_type: multi-GPU
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+ - num_devices: 8
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+ - total_train_batch_size: 128
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+ - total_eval_batch_size: 2048
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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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+ - lr_scheduler_warmup_steps: 200
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+ - num_epochs: 30
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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 | F1 Binary Minimum3 | F1 Binary Minimum2 |
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+ |:-------------:|:-------:|:------:|:---------------:|:---------:|:------:|:--------:|:--------:|:------------------:|:------------------:|
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+ | No log | 0 | 0 | 7.9458 | 0.0159 | 0.2 | 0.0294 | 0.0794 | 0 | 0 |
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+ | 0.3909 | 0.2932 | 1000 | 0.3869 | 0.6080 | 0.3401 | 0.3645 | 0.5781 | 0.7198 | 0.9645 |
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+ | 0.3743 | 0.5863 | 2000 | 0.3686 | 0.6224 | 0.3523 | 0.3809 | 0.5910 | 0.7154 | 0.9657 |
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+ | 0.3639 | 0.8795 | 3000 | 0.3666 | 0.6145 | 0.3529 | 0.3809 | 0.5920 | 0.7273 | 0.9657 |
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+ | 0.3655 | 1.1727 | 4000 | 0.3594 | 0.6360 | 0.3623 | 0.3946 | 0.5962 | 0.7145 | 0.9661 |
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+ | 0.3702 | 1.4658 | 5000 | 0.3585 | 0.6124 | 0.3566 | 0.3856 | 0.5960 | 0.7031 | 0.9663 |
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+ | 0.3625 | 1.7590 | 6000 | 0.3558 | 0.6531 | 0.3717 | 0.4082 | 0.5999 | 0.7191 | 0.9665 |
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+ | 0.3474 | 2.0522 | 7000 | 0.3542 | 0.6420 | 0.3696 | 0.4033 | 0.6004 | 0.7173 | 0.9666 |
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+ | 0.3711 | 2.3454 | 8000 | 0.3536 | 0.6375 | 0.3618 | 0.3944 | 0.5999 | 0.7107 | 0.9665 |
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+ | 0.3495 | 2.6385 | 9000 | 0.3522 | 0.6454 | 0.3736 | 0.4109 | 0.6021 | 0.7248 | 0.9667 |
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+ | 0.3576 | 2.9317 | 10000 | 0.3536 | 0.6591 | 0.3664 | 0.4012 | 0.6015 | 0.7305 | 0.9666 |
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+ | 0.3616 | 3.2249 | 11000 | 0.3558 | 0.6652 | 0.3813 | 0.4223 | 0.6011 | 0.7362 | 0.9666 |
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+ | 0.3482 | 3.5180 | 12000 | 0.3504 | 0.6589 | 0.3773 | 0.4163 | 0.6046 | 0.7259 | 0.9671 |
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+ | 0.3616 | 3.8112 | 13000 | 0.3550 | 0.6670 | 0.3889 | 0.4326 | 0.6036 | 0.7384 | 0.9666 |
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+ | 0.36 | 4.1044 | 14000 | 0.3515 | 0.6646 | 0.3844 | 0.4262 | 0.6049 | 0.7346 | 0.9671 |
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+ | 0.3553 | 4.3975 | 15000 | 0.3519 | 0.6779 | 0.3887 | 0.4336 | 0.6058 | 0.7369 | 0.9668 |
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+ | 0.3457 | 4.6907 | 16000 | 0.3485 | 0.6668 | 0.3852 | 0.4275 | 0.6049 | 0.7199 | 0.9671 |
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+ | 0.3544 | 4.9839 | 17000 | 0.3530 | 0.6510 | 0.3703 | 0.4043 | 0.5980 | 0.6881 | 0.9669 |
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+ | 0.349 | 5.2770 | 18000 | 0.3472 | 0.6650 | 0.3785 | 0.4184 | 0.6049 | 0.7189 | 0.9671 |
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+ | 0.3478 | 5.5702 | 19000 | 0.3479 | 0.6629 | 0.3709 | 0.4079 | 0.6038 | 0.7097 | 0.9669 |
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+ | 0.3517 | 5.8634 | 20000 | 0.3470 | 0.6630 | 0.3830 | 0.4265 | 0.6051 | 0.7154 | 0.9669 |
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+ | 0.3552 | 6.1566 | 21000 | 0.3475 | 0.6536 | 0.3767 | 0.4165 | 0.6041 | 0.7113 | 0.9667 |
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+ | 0.3619 | 6.4497 | 22000 | 0.3472 | 0.6705 | 0.3739 | 0.4127 | 0.6071 | 0.7275 | 0.9667 |
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+ | 0.3534 | 6.7429 | 23000 | 0.3626 | 0.6590 | 0.3978 | 0.4435 | 0.5977 | 0.7434 | 0.9667 |
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+ | 0.3494 | 7.0361 | 24000 | 0.3479 | 0.6711 | 0.3905 | 0.4363 | 0.6078 | 0.7312 | 0.9668 |
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+ | 0.3488 | 7.3292 | 25000 | 0.3455 | 0.6647 | 0.3836 | 0.4251 | 0.6075 | 0.7258 | 0.9671 |
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+ | 0.3557 | 7.6224 | 26000 | 0.3457 | 0.6699 | 0.3890 | 0.4328 | 0.6066 | 0.7193 | 0.9671 |
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+ | 0.3442 | 7.9156 | 27000 | 0.3461 | 0.6622 | 0.3726 | 0.4111 | 0.6060 | 0.7214 | 0.9671 |
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+ | 0.3648 | 8.2087 | 28000 | 0.3463 | 0.6742 | 0.3834 | 0.4260 | 0.6087 | 0.7310 | 0.9667 |
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+ | 0.35 | 8.5019 | 29000 | 0.3463 | 0.6577 | 0.3966 | 0.4434 | 0.6086 | 0.7317 | 0.9674 |
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+ | 0.3539 | 8.7951 | 30000 | 0.3526 | 0.6478 | 0.3654 | 0.3975 | 0.5977 | 0.6838 | 0.9669 |
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+ | 0.3475 | 9.0882 | 31000 | 0.3454 | 0.6761 | 0.3898 | 0.4352 | 0.6090 | 0.7326 | 0.9670 |
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+ | 0.3535 | 9.3814 | 32000 | 0.3447 | 0.6719 | 0.3895 | 0.4346 | 0.6092 | 0.7291 | 0.9671 |
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+ | 0.3514 | 9.6746 | 33000 | 0.3445 | 0.6660 | 0.3918 | 0.4380 | 0.6088 | 0.7281 | 0.9671 |
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+ | 0.3504 | 9.9678 | 34000 | 0.3455 | 0.6698 | 0.3914 | 0.4363 | 0.6094 | 0.7349 | 0.9672 |
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+ | 0.3629 | 10.2609 | 35000 | 0.3550 | 0.6620 | 0.3935 | 0.4389 | 0.6036 | 0.7441 | 0.9666 |
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+ | 0.3436 | 10.5541 | 36000 | 0.3491 | 0.6607 | 0.3959 | 0.4422 | 0.6074 | 0.7403 | 0.9672 |
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+ | 0.3516 | 10.8473 | 37000 | 0.3461 | 0.6641 | 0.3792 | 0.4166 | 0.6051 | 0.7062 | 0.9670 |
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+ | 0.3506 | 11.4336 | 39000 | 0.3450 | 0.6595 | 0.3969 | 0.4447 | 0.6101 | 0.7344 | 0.9672 |
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+ | 0.3372 | 15.2448 | 52000 | 0.3453 | 0.6706 | 0.3975 | 0.4449 | 0.6089 | 0.7375 | 0.9673 |
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+ | 0.3408 | 27.2647 | 93000 | 0.3405 | 0.6669 | 0.3925 | 0.4393 | 0.6100 | 0.7274 | 0.9672 |
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+ | 0.3424 | 27.8511 | 95000 | 0.3409 | 0.6664 | 0.3964 | 0.4445 | 0.6105 | 0.7318 | 0.9672 |
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+ | 0.3438 | 28.1442 | 96000 | 0.3405 | 0.6650 | 0.3942 | 0.4414 | 0.6109 | 0.7290 | 0.9672 |
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+ | 0.3328 | 28.4374 | 97000 | 0.3404 | 0.6640 | 0.3934 | 0.4401 | 0.6101 | 0.7220 | 0.9673 |
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+ | 0.3341 | 28.7306 | 98000 | 0.3405 | 0.6602 | 0.3951 | 0.4425 | 0.6107 | 0.7288 | 0.9673 |
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+ | 0.3377 | 29.3169 | 100000 | 0.3404 | 0.6614 | 0.3948 | 0.4422 | 0.6104 | 0.7278 | 0.9672 |
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+ | 0.3404 | 29.9033 | 102000 | 0.3403 | 0.6596 | 0.3962 | 0.4436 | 0.6112 | 0.7282 | 0.9673 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.43.4
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+ - Pytorch 2.4.0+cu121
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+ - Datasets 2.21.0
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+ - Tokenizers 0.19.1
final/config.json ADDED
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+ {
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+ "_name_or_path": "bigcode/starencoder",
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+ "architectures": [
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+ "BertForSequenceClassification"
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+ ],
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+ "model_type": "bert",
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+ "num_hidden_layers": 12,
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+ "pad_token_id": 49152,
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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": "4.43.4",
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+ "type_vocab_size": 2,
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+ "use_cache": true,
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+ "vocab_size": 49156
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+ }
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