Initial Commit
Browse files- README.md +175 -0
- config.json +153 -0
- pytorch_model.bin +3 -0
- training_args.bin +3 -0
README.md
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| 1 |
+
---
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| 2 |
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license: mit
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| 3 |
+
base_model: FacebookAI/xlm-roberta-base
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tags:
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| 5 |
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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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| 9 |
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- accuracy
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| 10 |
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- f1
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| 11 |
+
model-index:
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| 12 |
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- name: scenario-KD-SCR-MSV-D2_data-AmazonScience_massive_all_1_1_delta-jason
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| 13 |
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results: []
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| 14 |
+
---
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| 15 |
+
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| 16 |
+
<!-- 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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| 18 |
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# scenario-KD-SCR-MSV-D2_data-AmazonScience_massive_all_1_1_delta-jason
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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: 1.8042
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- Accuracy: 0.8264
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- F1: 0.8011
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## Model description
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More information needed
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| 30 |
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## Intended uses & limitations
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| 32 |
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| 33 |
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More information needed
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| 34 |
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| 35 |
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## Training and evaluation data
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| 36 |
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| 37 |
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More information needed
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| 39 |
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## Training procedure
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### Training hyperparameters
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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: 1254
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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| 49 |
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- lr_scheduler_type: linear
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- num_epochs: 30
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| 51 |
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| 52 |
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### Training results
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| 53 |
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| 54 |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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| 55 |
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|:-------------:|:-----:|:------:|:---------------:|:--------:|:------:|
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| 56 |
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| 5.7284 | 0.27 | 5000 | 5.5547 | 0.3495 | 0.1646 |
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| 3.9298 | 0.53 | 10000 | 3.9081 | 0.5831 | 0.4181 |
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| 3.1458 | 0.8 | 15000 | 3.1900 | 0.6691 | 0.5676 |
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| 2.53 | 1.07 | 20000 | 2.8419 | 0.7090 | 0.6229 |
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| 2.2929 | 1.34 | 25000 | 2.6332 | 0.7336 | 0.6597 |
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| 2.2133 | 1.6 | 30000 | 2.4526 | 0.7511 | 0.6781 |
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| 2.0478 | 1.87 | 35000 | 2.3194 | 0.7676 | 0.6988 |
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| 1.7304 | 2.14 | 40000 | 2.2969 | 0.7680 | 0.7101 |
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| 1.6742 | 2.41 | 45000 | 2.2247 | 0.7798 | 0.7297 |
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| 1.612 | 2.67 | 50000 | 2.1486 | 0.7869 | 0.7440 |
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| 1.593 | 2.94 | 55000 | 2.0761 | 0.7922 | 0.7491 |
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| 1.3076 | 3.21 | 60000 | 2.1148 | 0.7928 | 0.7532 |
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| 1.3084 | 3.47 | 65000 | 2.0691 | 0.7955 | 0.7546 |
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| 1.3439 | 3.74 | 70000 | 2.0406 | 0.7980 | 0.7577 |
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| 1.238 | 4.01 | 75000 | 2.0845 | 0.7962 | 0.7591 |
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| 1.1017 | 4.28 | 80000 | 2.0749 | 0.7999 | 0.7657 |
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| 1.113 | 4.54 | 85000 | 2.0310 | 0.8027 | 0.7682 |
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| 1.1233 | 4.81 | 90000 | 2.0350 | 0.8017 | 0.7667 |
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| 0.9201 | 5.08 | 95000 | 2.0900 | 0.8051 | 0.7668 |
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| 0.9371 | 5.34 | 100000 | 2.0517 | 0.8017 | 0.7716 |
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| 0.9407 | 5.61 | 105000 | 2.0891 | 0.8036 | 0.7747 |
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| 0.9562 | 5.88 | 110000 | 2.0128 | 0.8074 | 0.7743 |
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| 0.8116 | 6.15 | 115000 | 2.0271 | 0.8070 | 0.7747 |
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| 0.8406 | 6.41 | 120000 | 2.0704 | 0.8064 | 0.7772 |
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| 0.8337 | 6.68 | 125000 | 2.0371 | 0.8079 | 0.7794 |
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| 0.8457 | 6.95 | 130000 | 2.0188 | 0.8111 | 0.7883 |
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| 0.733 | 7.22 | 135000 | 2.0236 | 0.8124 | 0.7857 |
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| 0.7651 | 7.48 | 140000 | 2.0015 | 0.8093 | 0.7803 |
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| 0.7825 | 7.75 | 145000 | 2.0183 | 0.8085 | 0.7821 |
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| 0.675 | 8.02 | 150000 | 2.0356 | 0.8119 | 0.7844 |
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| 0.6616 | 8.28 | 155000 | 2.0042 | 0.8133 | 0.7859 |
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| 0.6763 | 8.55 | 160000 | 2.0247 | 0.8128 | 0.7856 |
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| 0.7017 | 8.82 | 165000 | 2.0063 | 0.8145 | 0.7892 |
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| 0.6238 | 9.09 | 170000 | 1.9923 | 0.8151 | 0.7870 |
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| 0.6246 | 9.35 | 175000 | 1.9945 | 0.8128 | 0.7861 |
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| 0.6149 | 9.62 | 180000 | 2.0137 | 0.8141 | 0.7857 |
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| 92 |
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| 0.6256 | 9.89 | 185000 | 2.0075 | 0.8144 | 0.7905 |
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| 0.6024 | 10.15 | 190000 | 1.9870 | 0.8156 | 0.7887 |
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| 94 |
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| 0.5943 | 10.42 | 195000 | 2.0002 | 0.8154 | 0.7909 |
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| 95 |
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| 0.6087 | 10.69 | 200000 | 1.9796 | 0.8142 | 0.7877 |
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| 96 |
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| 0.5841 | 10.96 | 205000 | 1.9951 | 0.8158 | 0.7917 |
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| 97 |
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| 0.5565 | 11.22 | 210000 | 1.9997 | 0.8147 | 0.7901 |
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| 98 |
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| 0.5517 | 11.49 | 215000 | 2.0010 | 0.8152 | 0.7928 |
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| 0.5594 | 11.76 | 220000 | 1.9900 | 0.8164 | 0.7885 |
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| 100 |
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| 0.5191 | 12.03 | 225000 | 1.9776 | 0.8139 | 0.7907 |
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| 0.5224 | 12.29 | 230000 | 1.9566 | 0.8170 | 0.7921 |
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| 0.5313 | 12.56 | 235000 | 1.9733 | 0.8188 | 0.7922 |
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| 0.5279 | 12.83 | 240000 | 1.9505 | 0.8172 | 0.7910 |
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| 104 |
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| 0.502 | 13.09 | 245000 | 1.9851 | 0.8164 | 0.7921 |
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| 105 |
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| 0.5004 | 13.36 | 250000 | 1.9504 | 0.8172 | 0.7936 |
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| 106 |
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| 0.505 | 13.63 | 255000 | 1.9244 | 0.8194 | 0.7907 |
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| 107 |
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| 0.499 | 13.9 | 260000 | 1.9605 | 0.8163 | 0.7905 |
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| 108 |
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| 0.4874 | 14.16 | 265000 | 1.9346 | 0.8196 | 0.7915 |
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| 109 |
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| 0.4825 | 14.43 | 270000 | 1.9360 | 0.8181 | 0.7932 |
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| 0.4973 | 14.7 | 275000 | 1.9251 | 0.8193 | 0.7952 |
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| 111 |
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| 0.4871 | 14.96 | 280000 | 1.9219 | 0.8200 | 0.7933 |
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| 112 |
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| 0.4524 | 15.23 | 285000 | 1.8977 | 0.8207 | 0.7955 |
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| 113 |
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| 0.4605 | 15.5 | 290000 | 1.9001 | 0.8201 | 0.7951 |
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| 114 |
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| 0.4625 | 15.77 | 295000 | 1.9227 | 0.8203 | 0.7966 |
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| 115 |
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| 0.4432 | 16.03 | 300000 | 1.9012 | 0.8214 | 0.7965 |
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| 116 |
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| 0.4448 | 16.3 | 305000 | 1.9161 | 0.8208 | 0.7978 |
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| 117 |
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| 0.4593 | 16.57 | 310000 | 1.8900 | 0.8211 | 0.7941 |
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| 118 |
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| 0.4518 | 16.84 | 315000 | 1.8960 | 0.8184 | 0.7936 |
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| 119 |
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| 0.4229 | 17.1 | 320000 | 1.9085 | 0.8208 | 0.7963 |
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| 120 |
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| 0.4366 | 17.37 | 325000 | 1.8767 | 0.8216 | 0.7981 |
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| 121 |
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| 0.4265 | 17.64 | 330000 | 1.8774 | 0.8233 | 0.7981 |
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| 122 |
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| 0.4342 | 17.9 | 335000 | 1.8915 | 0.8209 | 0.7960 |
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| 123 |
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| 0.4115 | 18.17 | 340000 | 1.8667 | 0.8236 | 0.7974 |
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| 124 |
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| 0.4147 | 18.44 | 345000 | 1.8752 | 0.8214 | 0.7936 |
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| 125 |
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| 0.4212 | 18.71 | 350000 | 1.8705 | 0.8220 | 0.7960 |
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| 126 |
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| 0.4196 | 18.97 | 355000 | 1.8663 | 0.8237 | 0.7992 |
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| 127 |
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| 0.3992 | 19.24 | 360000 | 1.8549 | 0.8236 | 0.7998 |
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| 128 |
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| 0.413 | 19.51 | 365000 | 1.8679 | 0.8229 | 0.7999 |
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| 129 |
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| 0.4048 | 19.77 | 370000 | 1.8594 | 0.8234 | 0.7977 |
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| 130 |
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| 0.396 | 20.04 | 375000 | 1.8530 | 0.8246 | 0.7981 |
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| 131 |
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| 0.398 | 20.31 | 380000 | 1.8536 | 0.8238 | 0.7995 |
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| 132 |
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| 0.3915 | 20.58 | 385000 | 1.8588 | 0.8233 | 0.7990 |
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| 133 |
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| 0.3961 | 20.84 | 390000 | 1.8726 | 0.8227 | 0.7981 |
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| 134 |
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| 0.3882 | 21.11 | 395000 | 1.8445 | 0.8236 | 0.7979 |
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| 135 |
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| 0.3844 | 21.38 | 400000 | 1.8465 | 0.8234 | 0.7983 |
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| 136 |
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| 0.3879 | 21.65 | 405000 | 1.8351 | 0.8244 | 0.7962 |
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| 137 |
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| 0.3904 | 21.91 | 410000 | 1.8457 | 0.8248 | 0.8002 |
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| 138 |
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| 0.3772 | 22.18 | 415000 | 1.8362 | 0.8255 | 0.8001 |
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| 139 |
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| 0.3802 | 22.45 | 420000 | 1.8277 | 0.8244 | 0.7989 |
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| 140 |
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| 0.3871 | 22.71 | 425000 | 1.8385 | 0.8236 | 0.7991 |
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| 141 |
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| 0.3806 | 22.98 | 430000 | 1.8390 | 0.8236 | 0.7985 |
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| 142 |
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| 0.3691 | 23.25 | 435000 | 1.8330 | 0.8237 | 0.7986 |
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| 143 |
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| 0.376 | 23.52 | 440000 | 1.8337 | 0.8247 | 0.7999 |
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| 144 |
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| 0.368 | 23.78 | 445000 | 1.8297 | 0.8254 | 0.8012 |
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| 145 |
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| 0.3607 | 24.05 | 450000 | 1.8294 | 0.8259 | 0.8008 |
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| 146 |
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| 0.3701 | 24.32 | 455000 | 1.8167 | 0.8254 | 0.7991 |
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| 147 |
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| 0.3621 | 24.58 | 460000 | 1.8322 | 0.8253 | 0.8004 |
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| 148 |
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| 0.3658 | 24.85 | 465000 | 1.8271 | 0.8249 | 0.7993 |
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| 149 |
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| 0.355 | 25.12 | 470000 | 1.8245 | 0.8267 | 0.8009 |
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| 150 |
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| 0.3662 | 25.39 | 475000 | 1.8205 | 0.8257 | 0.8004 |
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| 151 |
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| 0.3542 | 25.65 | 480000 | 1.8219 | 0.8256 | 0.7998 |
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| 152 |
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| 0.351 | 25.92 | 485000 | 1.8239 | 0.8246 | 0.7997 |
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| 153 |
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| 0.3536 | 26.19 | 490000 | 1.8072 | 0.8260 | 0.8008 |
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| 154 |
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| 0.3509 | 26.46 | 495000 | 1.8139 | 0.8255 | 0.8006 |
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| 155 |
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| 0.3503 | 26.72 | 500000 | 1.8121 | 0.8261 | 0.8008 |
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| 156 |
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| 0.359 | 26.99 | 505000 | 1.8133 | 0.8261 | 0.7993 |
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| 157 |
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| 0.3499 | 27.26 | 510000 | 1.8081 | 0.8265 | 0.8010 |
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| 158 |
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| 0.3428 | 27.52 | 515000 | 1.8061 | 0.8268 | 0.8011 |
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| 159 |
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| 0.3469 | 27.79 | 520000 | 1.8144 | 0.8258 | 0.8003 |
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| 160 |
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| 0.3364 | 28.06 | 525000 | 1.8063 | 0.8264 | 0.8011 |
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| 161 |
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| 0.347 | 28.33 | 530000 | 1.8071 | 0.8263 | 0.8006 |
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| 162 |
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| 0.3487 | 28.59 | 535000 | 1.8055 | 0.8262 | 0.8021 |
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| 163 |
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| 0.3406 | 28.86 | 540000 | 1.8062 | 0.8268 | 0.8022 |
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| 164 |
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| 0.3429 | 29.13 | 545000 | 1.8093 | 0.8264 | 0.8010 |
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| 165 |
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| 0.3392 | 29.39 | 550000 | 1.8011 | 0.8268 | 0.8014 |
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| 166 |
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| 0.3403 | 29.66 | 555000 | 1.8074 | 0.8264 | 0.8008 |
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| 167 |
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| 0.3424 | 29.93 | 560000 | 1.8042 | 0.8264 | 0.8011 |
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### Framework versions
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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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config.json
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|
|
| 1 |
+
{
|
| 2 |
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|
| 3 |
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|
| 4 |
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|
| 5 |
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|
| 6 |
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|
| 7 |
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|
| 11 |
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|
| 12 |
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| 22 |
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| 24 |
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| 29 |
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| 32 |
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| 33 |
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| 34 |
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| 57 |
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|
| 140 |
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|
| 141 |
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|
| 142 |
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|
| 143 |
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|
| 144 |
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|
| 145 |
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|
| 146 |
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|
| 147 |
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|
| 148 |
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|
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|
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|
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|
| 152 |
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|
| 153 |
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}
|
pytorch_model.bin
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:1f961b873728ccb569904ba0f81622c88937760419598f68585d480bef21eafb
|
| 3 |
+
size 429287542
|
training_args.bin
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
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| 2 |
+
oid sha256:9bf2db7666e40219908712f83979b9b0ca3c9d21237ed78a30ea2a73d4a65da5
|
| 3 |
+
size 4600
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