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llm-data-textbook-quality-classifier-v1

Text Classification
Transformers
Safetensors
English
xlm-roberta
Generated from Trainer
Inference Endpoints
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llm-data-quality-classifer-compare

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Files changed (9) hide show
  1. .gitattributes +1 -0
  2. README.md +190 -0
  3. clean.sh +13 -0
  4. config.json +37 -0
  5. model.safetensors +3 -0
  6. special_tokens_map.json +15 -0
  7. tokenizer.json +3 -0
  8. tokenizer_config.json +54 -0
  9. training_args.bin +3 -0
.gitattributes CHANGED
@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
 
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
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+ tokenizer.json filter=lfs diff=lfs merge=lfs -text
README.md ADDED
@@ -0,0 +1,190 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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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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+ - accuracy
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+ - precision
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+ - recall
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+ - f1
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+ model-index:
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+ - name: llm-data-quality-classifer-compare
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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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+ # llm-data-quality-classifer-compare
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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 an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.2689
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+ - Accuracy: 0.8833
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+ - Precision: 0.7551
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+ - Recall: 0.7598
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+ - F1: 0.7574
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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: 16
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+ - eval_batch_size: 16
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+ - seed: 42
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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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+ - num_epochs: 1
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Accuracy | F1 | Validation Loss | Precision | Recall |
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+ |:-------------:|:-----:|:-----:|:--------:|:------:|:---------------:|:---------:|:------:|
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+ | 0.4745 | 0.01 | 500 | 0.8076 | 0.6181 | 0.4327 | 0.5898 | 0.6493 |
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+ | 0.4088 | 0.02 | 1000 | 0.8346 | 0.5522 | 0.4287 | 0.7870 | 0.4254 |
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+ | 0.3811 | 0.02 | 1500 | 0.8286 | 0.6651 | 0.3741 | 0.6257 | 0.7098 |
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+ | 0.3762 | 0.03 | 2000 | 0.85 | 0.6529 | 0.3413 | 0.7334 | 0.5884 |
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+ | 0.3647 | 0.04 | 2500 | 0.8427 | 0.6632 | 0.3852 | 0.6815 | 0.6460 |
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+ | 0.3495 | 0.05 | 3000 | 0.8629 | 0.6987 | 0.3253 | 0.7385 | 0.6631 |
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+ | 0.3508 | 0.06 | 3500 | 0.8335 | 0.6967 | 0.3605 | 0.6186 | 0.7973 |
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+ | 0.3342 | 0.06 | 4000 | 0.8553 | 0.7075 | 0.3273 | 0.6865 | 0.7298 |
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+ | 0.341 | 0.07 | 4500 | 0.8602 | 0.6679 | 0.3320 | 0.7759 | 0.5863 |
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+ | 0.3344 | 0.08 | 5000 | 0.8531 | 0.6916 | 0.3441 | 0.6964 | 0.6868 |
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+ | 0.3341 | 0.09 | 5500 | 0.8536 | 0.7027 | 0.3265 | 0.6849 | 0.7214 |
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+ | 0.3319 | 0.1 | 6000 | 0.8599 | 0.7081 | 0.3266 | 0.7076 | 0.7085 |
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+ | 0.3259 | 0.1 | 6500 | 0.8136 | 0.6907 | 0.3908 | 0.5736 | 0.8678 |
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+ | 0.3391 | 0.11 | 7000 | 0.8642 | 0.6770 | 0.3338 | 0.7879 | 0.5934 |
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+ | 0.3207 | 0.12 | 7500 | 0.8668 | 0.7224 | 0.3035 | 0.7221 | 0.7227 |
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+ | 0.3191 | 0.13 | 8000 | 0.8543 | 0.7153 | 0.3179 | 0.6730 | 0.7631 |
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+ | 0.3142 | 0.14 | 8500 | 0.8679 | 0.7052 | 0.3101 | 0.7585 | 0.6589 |
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+ | 0.3195 | 0.14 | 9000 | 0.8636 | 0.7254 | 0.3433 | 0.7012 | 0.7515 |
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+ | 0.3196 | 0.15 | 9500 | 0.8707 | 0.7191 | 0.3048 | 0.7506 | 0.6902 |
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+ | 0.3176 | 0.16 | 10000 | 0.8597 | 0.7271 | 0.3177 | 0.6814 | 0.7794 |
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+ | 0.3218 | 0.17 | 10500 | 0.8723 | 0.6993 | 0.3212 | 0.8031 | 0.6193 |
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+ | 0.3175 | 0.18 | 11000 | 0.8601 | 0.7239 | 0.3366 | 0.6871 | 0.7648 |
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+ | 0.3296 | 0.18 | 11500 | 0.8526 | 0.7190 | 0.3218 | 0.6622 | 0.7865 |
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+ | 0.3249 | 0.19 | 12000 | 0.8731 | 0.7081 | 0.2926 | 0.7896 | 0.6418 |
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+ | 0.3141 | 0.2 | 12500 | 0.8741 | 0.7215 | 0.3035 | 0.7683 | 0.6802 |
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+ | 0.3126 | 0.21 | 13000 | 0.8659 | 0.7231 | 0.3127 | 0.7162 | 0.7302 |
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+ | 0.3204 | 0.22 | 13500 | 0.8665 | 0.7233 | 0.3456 | 0.7190 | 0.7277 |
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+ | 0.3108 | 0.22 | 14000 | 0.8674 | 0.7214 | 0.3018 | 0.7269 | 0.7160 |
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+ | 0.3114 | 0.23 | 14500 | 0.8726 | 0.7016 | 0.2967 | 0.8002 | 0.6247 |
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+ | 0.3071 | 0.24 | 15000 | 0.8768 | 0.7211 | 0.2904 | 0.7886 | 0.6643 |
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+ | 0.2965 | 0.25 | 15500 | 0.8674 | 0.7310 | 0.3126 | 0.7117 | 0.7515 |
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+ | 0.3022 | 0.26 | 16000 | 0.8738 | 0.7077 | 0.2887 | 0.7958 | 0.6372 |
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+ | 0.3101 | 0.26 | 16500 | 0.8559 | 0.7251 | 0.3312 | 0.6683 | 0.7923 |
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+ | 0.3154 | 0.27 | 17000 | 0.8575 | 0.7304 | 0.3221 | 0.6685 | 0.8048 |
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+ | 0.3041 | 0.28 | 17500 | 0.8754 | 0.7248 | 0.2864 | 0.7704 | 0.6843 |
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+ | 0.3093 | 0.29 | 18000 | 0.8603 | 0.7292 | 0.3101 | 0.6813 | 0.7844 |
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+ | 0.3006 | 0.3 | 18500 | 0.8753 | 0.7111 | 0.3008 | 0.7999 | 0.6401 |
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+ | 0.3108 | 0.3 | 19000 | 0.8689 | 0.7316 | 0.2911 | 0.7185 | 0.7452 |
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+ | 0.3071 | 0.31 | 19500 | 0.8793 | 0.7366 | 0.2839 | 0.7725 | 0.7039 |
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+ | 0.3002 | 0.32 | 20000 | 0.852 | 0.7239 | 0.3391 | 0.6550 | 0.8090 |
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+ | 0.301 | 0.33 | 20500 | 0.8769 | 0.7396 | 0.2896 | 0.7505 | 0.7289 |
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+ | 0.3075 | 0.34 | 21000 | 0.8785 | 0.7402 | 0.2891 | 0.7595 | 0.7219 |
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+ | 0.2922 | 0.34 | 21500 | 0.8393 | 0.7164 | 0.4094 | 0.6210 | 0.8465 |
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+ | 0.2973 | 0.35 | 22000 | 0.8787 | 0.7416 | 0.2962 | 0.7579 | 0.7260 |
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+ | 0.2987 | 0.36 | 22500 | 0.8711 | 0.7430 | 0.2983 | 0.7119 | 0.7769 |
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+ | 0.3071 | 0.37 | 23000 | 0.8739 | 0.7407 | 0.3167 | 0.7306 | 0.7510 |
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+ | 0.2846 | 0.38 | 23500 | 0.8801 | 0.7401 | 0.2901 | 0.7707 | 0.7118 |
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+ | 0.2924 | 0.38 | 24000 | 0.863 | 0.7299 | 0.3155 | 0.6922 | 0.7719 |
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+ | 0.2998 | 0.46 | 29000 | 0.874 | 0.7403 | 0.2893 | 0.7319 | 0.7490 |
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+ | 0.2875 | 0.47 | 29500 | 0.8803 | 0.7422 | 0.2891 | 0.7675 | 0.7185 |
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+ | 0.2946 | 0.48 | 30000 | 0.2781 | 0.8798 | 0.7415 | 0.7656 | 0.7534 |
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+ | 0.2907 | 0.49 | 30500 | 0.2860 | 0.8752 | 0.7280 | 0.7656 | 0.7463 |
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+ | 0.2981 | 0.5 | 31000 | 0.3012 | 0.8732 | 0.7276 | 0.7531 | 0.7402 |
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+ | 0.2948 | 0.5 | 31500 | 0.2777 | 0.8792 | 0.7894 | 0.6768 | 0.7288 |
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+ | 0.2933 | 0.51 | 32000 | 0.2839 | 0.8773 | 0.7428 | 0.7469 | 0.7449 |
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+ | 0.2891 | 0.52 | 32500 | 0.2774 | 0.8795 | 0.7678 | 0.7131 | 0.7395 |
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+ | 0.2869 | 0.53 | 33000 | 0.2790 | 0.8764 | 0.7405 | 0.7460 | 0.7432 |
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+ | 0.2907 | 0.54 | 33500 | 0.2889 | 0.8764 | 0.7580 | 0.7118 | 0.7342 |
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+ | 0.2912 | 0.54 | 34000 | 0.2887 | 0.8807 | 0.7464 | 0.7611 | 0.7537 |
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+ | 0.283 | 0.55 | 34500 | 0.2754 | 0.8816 | 0.7847 | 0.6977 | 0.7386 |
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+ | 0.2877 | 0.56 | 35000 | 0.3036 | 0.8727 | 0.7221 | 0.7627 | 0.7418 |
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+ | 0.2923 | 0.57 | 35500 | 0.2853 | 0.8783 | 0.7693 | 0.7035 | 0.7349 |
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+ | 0.2902 | 0.58 | 36000 | 0.2881 | 0.8772 | 0.7462 | 0.7394 | 0.7428 |
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+ | 0.2863 | 0.58 | 36500 | 0.2886 | 0.8768 | 0.7303 | 0.7711 | 0.7501 |
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+ | 0.2837 | 0.59 | 37000 | 0.2753 | 0.8801 | 0.7503 | 0.7494 | 0.7498 |
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+ | 0.3021 | 0.6 | 37500 | 0.2848 | 0.8775 | 0.7330 | 0.7694 | 0.7508 |
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+ | 0.291 | 0.61 | 38000 | 0.2793 | 0.88 | 0.7423 | 0.7652 | 0.7536 |
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+ | 0.2821 | 0.62 | 38500 | 0.2867 | 0.88 | 0.7429 | 0.7640 | 0.7533 |
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+ | 0.2867 | 0.62 | 39000 | 0.2851 | 0.8796 | 0.7367 | 0.7748 | 0.7553 |
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+ | 0.2846 | 0.63 | 39500 | 0.2813 | 0.8828 | 0.7661 | 0.7360 | 0.7507 |
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+ | 0.2835 | 0.65 | 40500 | 0.2797 | 0.8792 | 0.7382 | 0.7690 | 0.7533 |
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+ | 0.2833 | 0.66 | 41000 | 0.2763 | 0.8821 | 0.7895 | 0.6931 | 0.7382 |
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+ | 0.2743 | 0.66 | 41500 | 0.2852 | 0.8833 | 0.7717 | 0.7289 | 0.7497 |
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+ | 0.2844 | 0.79 | 49500 | 0.2877 | 0.8762 | 0.7215 | 0.7877 | 0.7532 |
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+ | 0.2795 | 0.82 | 51000 | 0.2755 | 0.8856 | 0.7876 | 0.7160 | 0.7501 |
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+ | 0.2649 | 0.82 | 51500 | 0.2797 | 0.8805 | 0.7360 | 0.7823 | 0.7584 |
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+ | 0.2675 | 0.86 | 53500 | 0.2742 | 0.8785 | 0.7392 | 0.7623 | 0.7506 |
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+ | 0.2745 | 0.88 | 55000 | 0.2751 | 0.8792 | 0.7348 | 0.7765 | 0.7551 |
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+ | 0.273 | 0.89 | 55500 | 0.2762 | 0.8812 | 0.7388 | 0.7807 | 0.7591 |
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+ | 0.2645 | 0.9 | 56000 | 0.2664 | 0.8828 | 0.7647 | 0.7385 | 0.7514 |
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+ | 0.2698 | 0.9 | 56500 | 0.2728 | 0.8814 | 0.7467 | 0.7648 | 0.7557 |
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+ | 0.2771 | 0.91 | 57000 | 0.2681 | 0.8839 | 0.7635 | 0.7473 | 0.7553 |
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+ | 0.2663 | 0.92 | 57500 | 0.2715 | 0.885 | 0.7617 | 0.7573 | 0.7595 |
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+ | 0.2546 | 0.93 | 58000 | 0.2836 | 0.8796 | 0.7323 | 0.7848 | 0.7576 |
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+ | 0.2752 | 0.94 | 58500 | 0.2747 | 0.8801 | 0.7363 | 0.7790 | 0.7570 |
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+ | 0.2645 | 0.94 | 59000 | 0.2733 | 0.8834 | 0.7484 | 0.7740 | 0.7610 |
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+ | 0.2561 | 0.95 | 59500 | 0.2765 | 0.8828 | 0.7508 | 0.7652 | 0.7580 |
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+ | 0.2753 | 0.96 | 60000 | 0.2721 | 0.8815 | 0.7483 | 0.7623 | 0.7552 |
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+ | 0.251 | 0.97 | 60500 | 0.2735 | 0.8822 | 0.7546 | 0.7540 | 0.7543 |
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+ | 0.2742 | 0.98 | 61000 | 0.2721 | 0.8831 | 0.7497 | 0.7694 | 0.7594 |
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+ | 0.2713 | 0.99 | 62000 | 0.2690 | 0.8836 | 0.7556 | 0.7606 | 0.7581 |
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+ | 0.2764 | 1.0 | 62500 | 0.2689 | 0.8833 | 0.7551 | 0.7598 | 0.7574 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.2
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+ - Pytorch 2.1.0+cu121
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+ - Datasets 2.16.1
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+ - Tokenizers 0.15.0
clean.sh ADDED
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+ #!/bin/bash
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+
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+ while true
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+ do
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+ latest_folder=$(ls -td */ | head -n 1)
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+
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+ for folder in */; do
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+ if [ $folder != $latest_folder ]; then
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+ rm -rf $folder
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+ fi
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+ done
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+ sleep 300
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+ done
config.json ADDED
@@ -0,0 +1,37 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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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+ ],
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+ "attention_probs_dropout_prob": 0.1,
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+ "bos_token_id": 0,
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+ "classifier_dropout": null,
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+ "eos_token_id": 2,
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+ "hidden_act": "gelu",
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+ "hidden_dropout_prob": 0.1,
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+ "hidden_size": 768,
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+ "id2label": {
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+ "0": "LOW_QUALITY",
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+ "1": "HIGH_QUALITY"
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+ },
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+ "initializer_range": 0.02,
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+ "intermediate_size": 3072,
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+ "label2id": {
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+ "HIGH_QUALITY": 1,
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+ "LOW_QUALITY": 0
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+ },
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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": "single_label_classification",
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.35.2",
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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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+ "cls_token": "<s>",
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+ "eos_token": "</s>",
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+ "mask_token": {
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+ "content": "<mask>",
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+ "sep_token": "</s>",
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+ "unk_token": "<unk>"
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+ }
tokenizer.json ADDED
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