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scenario-KD-SCR-MSV-D2_data-AmazonScience_massive_all_1_1_gamma-jason

Transformers
PyTorch
xlm-roberta
Generated from Trainer
Inference Endpoints
Model card Files Community
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  1. README.md +175 -0
  2. config.json +153 -0
  3. pytorch_model.bin +3 -0
  4. training_args.bin +3 -0
README.md ADDED
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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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+ datasets:
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+ - massive
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+ metrics:
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+ - accuracy
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+ - f1
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+ model-index:
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+ - name: scenario-KD-SCR-MSV-D2_data-AmazonScience_massive_all_1_1_gamma-jason
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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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+ # scenario-KD-SCR-MSV-D2_data-AmazonScience_massive_all_1_1_gamma-jason
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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 massive dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.8136
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+ - Accuracy: 0.8249
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+ - F1: 0.8012
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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: 32
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+ - eval_batch_size: 32
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+ - seed: 123621
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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: 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 | Accuracy | F1 |
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+ |:-------------:|:-----:|:------:|:---------------:|:--------:|:------:|
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+ | 5.9639 | 0.27 | 5000 | 5.8995 | 0.2955 | 0.1146 |
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+ | 4.2158 | 0.53 | 10000 | 4.1658 | 0.5475 | 0.3812 |
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+ | 3.2469 | 0.8 | 15000 | 3.3199 | 0.6523 | 0.5316 |
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+ | 2.5924 | 1.07 | 20000 | 2.8985 | 0.7018 | 0.6127 |
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+ | 2.359 | 1.34 | 25000 | 2.6534 | 0.7297 | 0.6595 |
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+ | 2.1928 | 1.6 | 30000 | 2.4466 | 0.7556 | 0.6969 |
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+ | 2.0695 | 1.87 | 35000 | 2.2808 | 0.7719 | 0.7201 |
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+ | 1.6893 | 2.14 | 40000 | 2.3052 | 0.7714 | 0.7085 |
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+ | 1.6663 | 2.41 | 45000 | 2.2096 | 0.7796 | 0.7274 |
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+ | 1.6035 | 2.67 | 50000 | 2.1603 | 0.7821 | 0.7388 |
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+ | 1.5974 | 2.94 | 55000 | 2.1085 | 0.7886 | 0.7445 |
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+ | 1.3064 | 3.21 | 60000 | 2.1031 | 0.7949 | 0.7541 |
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+ | 1.2976 | 3.47 | 65000 | 2.0789 | 0.7939 | 0.7503 |
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+ | 1.3204 | 3.74 | 70000 | 2.0467 | 0.7973 | 0.7608 |
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+ | 1.2155 | 4.01 | 75000 | 2.0445 | 0.8029 | 0.7624 |
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+ | 1.1162 | 4.28 | 80000 | 2.0914 | 0.8000 | 0.7638 |
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+ | 1.0772 | 4.54 | 85000 | 2.0247 | 0.8022 | 0.7668 |
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+ | 1.087 | 4.81 | 90000 | 1.9932 | 0.8044 | 0.7715 |
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+ | 0.9072 | 5.08 | 95000 | 2.0550 | 0.8049 | 0.7720 |
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+ | 0.948 | 5.34 | 100000 | 2.0583 | 0.8037 | 0.7737 |
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+ | 0.9416 | 5.61 | 105000 | 2.0447 | 0.8048 | 0.7738 |
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+ | 0.9495 | 5.88 | 110000 | 2.0402 | 0.8035 | 0.7725 |
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+ | 0.8017 | 6.15 | 115000 | 2.0705 | 0.8043 | 0.7743 |
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+ | 0.8167 | 6.41 | 120000 | 2.0509 | 0.8098 | 0.7820 |
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+ | 0.8453 | 6.68 | 125000 | 2.0258 | 0.8083 | 0.7797 |
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+ | 0.8504 | 6.95 | 130000 | 2.0039 | 0.8094 | 0.7815 |
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+ | 0.7261 | 7.22 | 135000 | 2.0579 | 0.8099 | 0.7814 |
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+ | 0.7351 | 7.48 | 140000 | 2.0215 | 0.8118 | 0.7814 |
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+ | 0.7607 | 7.75 | 145000 | 1.9842 | 0.8126 | 0.7807 |
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+ | 0.6825 | 8.02 | 150000 | 2.0317 | 0.8125 | 0.7833 |
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+ | 0.6747 | 8.28 | 155000 | 2.0287 | 0.8103 | 0.7833 |
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+ | 0.6759 | 8.55 | 160000 | 2.0570 | 0.8109 | 0.7850 |
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+ | 0.6915 | 8.82 | 165000 | 2.0286 | 0.8107 | 0.7850 |
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+ | 0.6121 | 9.09 | 170000 | 2.0231 | 0.8128 | 0.7871 |
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+ | 0.6033 | 9.35 | 175000 | 1.9958 | 0.8132 | 0.7861 |
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+ | 0.6238 | 9.62 | 180000 | 2.0033 | 0.8127 | 0.7893 |
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+ | 0.6388 | 9.89 | 185000 | 1.9964 | 0.8126 | 0.7869 |
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+ | 0.5685 | 10.15 | 190000 | 1.9832 | 0.8152 | 0.7915 |
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+ | 0.5809 | 10.42 | 195000 | 1.9936 | 0.8143 | 0.7901 |
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+ | 0.5918 | 10.69 | 200000 | 1.9799 | 0.8154 | 0.7921 |
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+ | 0.5935 | 10.96 | 205000 | 2.0006 | 0.8142 | 0.7910 |
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+ | 0.5453 | 11.22 | 210000 | 1.9909 | 0.8149 | 0.7906 |
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+ | 0.5617 | 11.49 | 215000 | 1.9938 | 0.8163 | 0.7887 |
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+ | 0.5612 | 11.76 | 220000 | 1.9629 | 0.8164 | 0.7911 |
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+ | 0.5285 | 12.03 | 225000 | 1.9658 | 0.8162 | 0.7915 |
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+ | 0.5264 | 12.29 | 230000 | 1.9494 | 0.8161 | 0.7916 |
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+ | 0.5204 | 12.56 | 235000 | 1.9663 | 0.8162 | 0.7918 |
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+ | 0.5371 | 12.83 | 240000 | 1.9591 | 0.8180 | 0.7938 |
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+ | 0.4888 | 13.09 | 245000 | 1.9480 | 0.8188 | 0.7939 |
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+ | 0.5061 | 13.36 | 250000 | 1.9505 | 0.8180 | 0.7936 |
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+ | 0.5071 | 13.63 | 255000 | 1.9220 | 0.8185 | 0.7925 |
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+ | 0.5169 | 13.9 | 260000 | 1.9130 | 0.8185 | 0.7931 |
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+ | 0.4841 | 14.16 | 265000 | 1.9376 | 0.8176 | 0.7926 |
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+ | 0.4848 | 14.43 | 270000 | 1.9286 | 0.8185 | 0.7970 |
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+ | 0.4892 | 14.7 | 275000 | 1.9307 | 0.8192 | 0.7988 |
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+ | 0.4812 | 14.96 | 280000 | 1.9178 | 0.8204 | 0.7992 |
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+ | 0.4715 | 15.23 | 285000 | 1.9250 | 0.8183 | 0.7957 |
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+ | 0.4555 | 15.5 | 290000 | 1.9070 | 0.8192 | 0.7945 |
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+ | 0.459 | 15.77 | 295000 | 1.9043 | 0.8197 | 0.7988 |
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+ | 0.4421 | 16.03 | 300000 | 1.9107 | 0.8200 | 0.7989 |
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+ | 0.4409 | 16.3 | 305000 | 1.9116 | 0.8205 | 0.7965 |
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+ | 0.4446 | 16.57 | 310000 | 1.9168 | 0.8187 | 0.7955 |
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+ | 0.4555 | 16.84 | 315000 | 1.9092 | 0.8196 | 0.7955 |
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+ | 0.4366 | 17.1 | 320000 | 1.8796 | 0.8226 | 0.7998 |
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+ | 0.4281 | 17.37 | 325000 | 1.8841 | 0.8217 | 0.7965 |
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+ | 0.4334 | 17.9 | 335000 | 1.8906 | 0.8206 | 0.8002 |
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+ | 0.4145 | 18.17 | 340000 | 1.8844 | 0.8210 | 0.7973 |
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+ | 0.4159 | 18.44 | 345000 | 1.8848 | 0.8220 | 0.7992 |
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+ | 0.4226 | 18.71 | 350000 | 1.8813 | 0.8213 | 0.7990 |
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+ | 0.425 | 18.97 | 355000 | 1.8698 | 0.8226 | 0.7970 |
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+ | 0.4056 | 19.24 | 360000 | 1.8689 | 0.8225 | 0.7990 |
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+ | 0.373 | 22.18 | 415000 | 1.8472 | 0.8238 | 0.8003 |
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+ | 0.3842 | 22.45 | 420000 | 1.8446 | 0.8236 | 0.7992 |
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+ | 0.3761 | 22.71 | 425000 | 1.8393 | 0.8252 | 0.8019 |
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+ | 0.3742 | 22.98 | 430000 | 1.8391 | 0.8239 | 0.7995 |
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+ | 0.3708 | 23.25 | 435000 | 1.8248 | 0.8253 | 0.8035 |
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+ | 0.3705 | 23.52 | 440000 | 1.8345 | 0.8243 | 0.8001 |
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+ | 0.3416 | 29.66 | 555000 | 1.8062 | 0.8254 | 0.8013 |
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+ | 0.3387 | 29.93 | 560000 | 1.8136 | 0.8249 | 0.8012 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.33.3
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+ - Pytorch 2.1.1+cu121
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+ - Datasets 2.14.5
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+ - Tokenizers 0.13.3
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+ {
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+ "XLMRobertaForSequenceClassificationKD"
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