Commit
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Parent(s):
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Baktashans/Finetuned_xlmroberta_large_ArmanEmo
Browse files- README.md +16 -135
- config.json +15 -12
- model.safetensors +2 -2
- training_args.bin +1 -1
README.md
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---
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license:
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base_model:
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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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- f1
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- accuracy
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model-index:
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- name: results
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results: []
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# results
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This model is a fine-tuned version of [
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It achieves the following results on the evaluation set:
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## Model description
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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:
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- eval_batch_size:
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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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- lr_scheduler_warmup_steps: 500
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- num_epochs: 3
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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| 2.0887 | 0.03 | 10 | 2.0154 | 0.1026 | 0.0660 | 0.0374 | 0.0660 |
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| 2.0188 | 0.05 | 20 | 1.9896 | 0.1714 | 0.0834 | 0.0656 | 0.0834 |
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| 1.935 | 0.08 | 30 | 1.9582 | 0.2681 | 0.1225 | 0.1065 | 0.1225 |
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| 1.9276 | 0.1 | 40 | 1.9479 | 0.2919 | 0.1520 | 0.0904 | 0.1520 |
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| 1.9172 | 0.13 | 50 | 1.9575 | 0.2939 | 0.1607 | 0.0533 | 0.1607 |
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| 1.8547 | 0.16 | 60 | 1.9530 | 0.3070 | 0.1659 | 0.0529 | 0.1659 |
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| 1.936 | 0.18 | 70 | 1.9161 | 0.3009 | 0.1712 | 0.0645 | 0.1712 |
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| 1.8457 | 0.21 | 80 | 1.8840 | 0.2409 | 0.1772 | 0.0813 | 0.1772 |
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| 1.8319 | 0.23 | 90 | 1.8365 | 0.4240 | 0.1990 | 0.1241 | 0.1990 |
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| 1.835 | 0.26 | 100 | 1.8158 | 0.3236 | 0.2415 | 0.1944 | 0.2415 |
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| 1.7825 | 0.29 | 110 | 1.8553 | 0.2811 | 0.2285 | 0.1363 | 0.2285 |
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| 1.7324 | 0.31 | 120 | 1.8726 | 0.2696 | 0.1998 | 0.1075 | 0.1998 |
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| 1.7284 | 0.34 | 130 | 1.8401 | 0.4961 | 0.2146 | 0.1357 | 0.2146 |
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| 1.6867 | 0.37 | 140 | 1.8125 | 0.4280 | 0.2094 | 0.1234 | 0.2094 |
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| 1.6612 | 0.39 | 150 | 1.8338 | 0.3749 | 0.2381 | 0.1630 | 0.2381 |
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| 1.6787 | 0.42 | 160 | 1.7271 | 0.4411 | 0.3440 | 0.3089 | 0.3440 |
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| 1.5569 | 0.44 | 170 | 1.6722 | 0.4984 | 0.3189 | 0.2876 | 0.3189 |
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| 1.4984 | 0.47 | 180 | 1.6449 | 0.5349 | 0.3449 | 0.3206 | 0.3449 |
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| 1.4869 | 0.5 | 190 | 1.5898 | 0.5395 | 0.3901 | 0.3666 | 0.3901 |
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| 1.4717 | 0.52 | 200 | 1.5222 | 0.5695 | 0.4361 | 0.4031 | 0.4361 |
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| 1.3203 | 0.55 | 210 | 1.5364 | 0.5429 | 0.3884 | 0.3693 | 0.3884 |
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| 1.3388 | 0.57 | 220 | 1.4703 | 0.5329 | 0.4179 | 0.4043 | 0.4179 |
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| 1.1816 | 0.6 | 230 | 1.4253 | 0.5720 | 0.4483 | 0.4370 | 0.4483 |
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| 1.2284 | 0.63 | 240 | 1.4765 | 0.5287 | 0.4083 | 0.3800 | 0.4083 |
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| 1.2556 | 0.65 | 250 | 1.4229 | 0.5414 | 0.4474 | 0.4318 | 0.4474 |
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| 1.189 | 0.68 | 260 | 1.3329 | 0.5695 | 0.5135 | 0.5119 | 0.5135 |
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| 1.1864 | 0.7 | 270 | 1.3007 | 0.5594 | 0.5143 | 0.4970 | 0.5143 |
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| 0.9845 | 0.73 | 280 | 1.4464 | 0.5749 | 0.4109 | 0.3995 | 0.4109 |
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| 1.0829 | 0.76 | 290 | 1.2253 | 0.5583 | 0.5543 | 0.5483 | 0.5543 |
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| 1.0458 | 0.78 | 300 | 1.3545 | 0.5819 | 0.4996 | 0.4926 | 0.4996 |
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| 1.041 | 0.81 | 310 | 1.2830 | 0.5832 | 0.5282 | 0.5244 | 0.5282 |
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| 1.0827 | 0.84 | 320 | 1.2465 | 0.5980 | 0.5395 | 0.5426 | 0.5395 |
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| 1.0607 | 0.86 | 330 | 1.2328 | 0.6094 | 0.5725 | 0.5639 | 0.5725 |
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| 0.9246 | 0.89 | 340 | 1.3451 | 0.6162 | 0.4900 | 0.4859 | 0.4900 |
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| 1.0632 | 0.91 | 350 | 1.2458 | 0.6199 | 0.5613 | 0.5612 | 0.5613 |
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| 0.9418 | 0.94 | 360 | 1.2298 | 0.6465 | 0.5830 | 0.5825 | 0.5830 |
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| 0.863 | 0.97 | 370 | 1.3091 | 0.6104 | 0.5421 | 0.5347 | 0.5421 |
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| 1.0733 | 0.99 | 380 | 1.1668 | 0.6016 | 0.6012 | 0.5955 | 0.6012 |
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| 0.9344 | 1.02 | 390 | 1.2569 | 0.5894 | 0.5361 | 0.5286 | 0.5361 |
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| 0.8471 | 1.04 | 400 | 1.3994 | 0.5895 | 0.4805 | 0.4520 | 0.4805 |
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| 0.8702 | 1.07 | 410 | 1.2192 | 0.5945 | 0.5760 | 0.5759 | 0.5760 |
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| 0.7876 | 1.1 | 420 | 1.2214 | 0.5963 | 0.5708 | 0.5679 | 0.5708 |
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| 0.7738 | 1.12 | 430 | 1.4516 | 0.6112 | 0.4987 | 0.4815 | 0.4987 |
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| 0.8228 | 1.15 | 440 | 1.1970 | 0.6287 | 0.5899 | 0.5939 | 0.5899 |
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| 0.875 | 1.17 | 450 | 1.3629 | 0.6326 | 0.5117 | 0.5129 | 0.5117 |
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| 0.7296 | 1.2 | 460 | 1.1241 | 0.6391 | 0.6177 | 0.6161 | 0.6177 |
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| 0.9765 | 1.23 | 470 | 1.3897 | 0.6501 | 0.5239 | 0.5092 | 0.5239 |
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| 0.8082 | 1.25 | 480 | 1.2875 | 0.6487 | 0.5404 | 0.5275 | 0.5404 |
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| 0.8403 | 1.28 | 490 | 1.2767 | 0.6092 | 0.5665 | 0.5507 | 0.5665 |
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| 1.0234 | 1.31 | 500 | 1.2761 | 0.6408 | 0.5552 | 0.5431 | 0.5552 |
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| 0.7822 | 1.33 | 510 | 1.1487 | 0.6559 | 0.5986 | 0.6010 | 0.5986 |
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| 1.004 | 1.36 | 520 | 1.0924 | 0.6369 | 0.6290 | 0.6262 | 0.6290 |
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| 0.9674 | 1.38 | 530 | 1.4964 | 0.6596 | 0.4205 | 0.4165 | 0.4205 |
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| 0.913 | 1.41 | 540 | 1.0923 | 0.6198 | 0.6064 | 0.5975 | 0.6064 |
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| 0.843 | 1.44 | 550 | 1.1285 | 0.6540 | 0.5934 | 0.5962 | 0.5934 |
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| 0.9108 | 1.46 | 560 | 1.2013 | 0.6685 | 0.5595 | 0.5628 | 0.5595 |
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| 0.9457 | 1.49 | 570 | 1.0782 | 0.6565 | 0.6325 | 0.6313 | 0.6325 |
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| 0.8657 | 1.51 | 580 | 1.1828 | 0.6507 | 0.5699 | 0.5586 | 0.5699 |
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| 0.738 | 1.54 | 590 | 1.1792 | 0.6678 | 0.5786 | 0.5888 | 0.5786 |
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| 0.8828 | 1.57 | 600 | 1.0729 | 0.6648 | 0.6429 | 0.6444 | 0.6429 |
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| 0.9846 | 1.59 | 610 | 1.0605 | 0.6396 | 0.6290 | 0.6276 | 0.6290 |
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| 0.8118 | 1.62 | 620 | 1.2294 | 0.6645 | 0.5552 | 0.5555 | 0.5552 |
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| 0.8287 | 1.64 | 630 | 1.1700 | 0.6402 | 0.5925 | 0.5939 | 0.5925 |
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| 0.8296 | 1.67 | 640 | 1.2598 | 0.6265 | 0.5647 | 0.5639 | 0.5647 |
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| 0.8129 | 1.7 | 650 | 1.1715 | 0.6256 | 0.5830 | 0.5876 | 0.5830 |
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| 0.8513 | 1.72 | 660 | 1.1968 | 0.6390 | 0.5699 | 0.5660 | 0.5699 |
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| 0.9274 | 1.75 | 670 | 1.2847 | 0.6653 | 0.5456 | 0.5421 | 0.5456 |
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| 0.9123 | 1.78 | 680 | 1.1750 | 0.6653 | 0.5812 | 0.5884 | 0.5812 |
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| 0.8918 | 1.8 | 690 | 1.0037 | 0.6452 | 0.6360 | 0.6326 | 0.6360 |
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| 0.8616 | 1.83 | 700 | 1.0693 | 0.6671 | 0.6334 | 0.6340 | 0.6334 |
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| 0.7689 | 1.85 | 710 | 1.1315 | 0.6429 | 0.6003 | 0.5958 | 0.6003 |
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| 0.9382 | 1.88 | 720 | 1.0789 | 0.6651 | 0.6403 | 0.6405 | 0.6403 |
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| 0.7599 | 1.91 | 730 | 1.2471 | 0.6338 | 0.5482 | 0.5555 | 0.5482 |
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| 0.8302 | 1.93 | 740 | 1.1304 | 0.6588 | 0.6090 | 0.6116 | 0.6090 |
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| 0.8508 | 1.96 | 750 | 1.1509 | 0.6612 | 0.6030 | 0.5989 | 0.6030 |
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| 0.9708 | 1.98 | 760 | 1.1143 | 0.6633 | 0.6038 | 0.6012 | 0.6038 |
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| 0.6454 | 2.01 | 770 | 1.1169 | 0.6596 | 0.5960 | 0.5981 | 0.5960 |
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| 0.3702 | 2.04 | 780 | 1.0938 | 0.6579 | 0.6186 | 0.6147 | 0.6186 |
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| 0.4184 | 2.06 | 790 | 1.1759 | 0.6495 | 0.6030 | 0.5999 | 0.6030 |
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| 0.5047 | 2.09 | 800 | 1.1226 | 0.6688 | 0.6316 | 0.6331 | 0.6316 |
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| 0.3472 | 2.11 | 810 | 1.0946 | 0.6746 | 0.6360 | 0.6396 | 0.6360 |
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| 0.4132 | 2.14 | 820 | 1.1737 | 0.6884 | 0.6342 | 0.6373 | 0.6342 |
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| 0.4315 | 2.17 | 830 | 1.1985 | 0.6687 | 0.6316 | 0.6241 | 0.6316 |
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| 0.4124 | 2.19 | 840 | 1.1992 | 0.6564 | 0.6125 | 0.6113 | 0.6125 |
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| 0.3832 | 2.22 | 850 | 1.2073 | 0.6585 | 0.6151 | 0.6182 | 0.6151 |
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| 0.5392 | 2.25 | 860 | 1.1951 | 0.6540 | 0.6082 | 0.6108 | 0.6082 |
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| 0.5386 | 2.27 | 870 | 1.2127 | 0.6690 | 0.6169 | 0.6180 | 0.6169 |
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| 0.3711 | 2.3 | 880 | 1.2248 | 0.6557 | 0.6047 | 0.6034 | 0.6047 |
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| 0.373 | 2.32 | 890 | 1.2216 | 0.6740 | 0.6108 | 0.6126 | 0.6108 |
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| 0.4399 | 2.35 | 900 | 1.1787 | 0.6699 | 0.6160 | 0.6174 | 0.6160 |
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| 0.403 | 2.38 | 910 | 1.1344 | 0.6707 | 0.6351 | 0.6355 | 0.6351 |
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| 0.334 | 2.4 | 920 | 1.1848 | 0.6734 | 0.6238 | 0.6273 | 0.6238 |
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| 0.3405 | 2.43 | 930 | 1.1958 | 0.6779 | 0.6221 | 0.6263 | 0.6221 |
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| 0.3062 | 2.45 | 940 | 1.2068 | 0.6742 | 0.6264 | 0.6283 | 0.6264 |
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| 0.4048 | 2.48 | 950 | 1.2888 | 0.6777 | 0.6116 | 0.6112 | 0.6116 |
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| 0.4005 | 2.51 | 960 | 1.1962 | 0.6842 | 0.6360 | 0.6411 | 0.6360 |
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| 0.2992 | 2.53 | 970 | 1.1667 | 0.6788 | 0.6351 | 0.6394 | 0.6351 |
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| 0.2881 | 2.56 | 980 | 1.2151 | 0.6766 | 0.6238 | 0.6284 | 0.6238 |
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| 0.2876 | 2.58 | 990 | 1.2049 | 0.6815 | 0.6299 | 0.6342 | 0.6299 |
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| 0.5007 | 2.61 | 1000 | 1.1878 | 0.6804 | 0.6368 | 0.6402 | 0.6368 |
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| 0.3416 | 2.64 | 1010 | 1.1477 | 0.6817 | 0.6473 | 0.6486 | 0.6473 |
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| 0.4522 | 2.66 | 1020 | 1.1605 | 0.6813 | 0.6473 | 0.6476 | 0.6473 |
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| 0.3734 | 2.69 | 1030 | 1.1724 | 0.6834 | 0.6455 | 0.6483 | 0.6455 |
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| 0.519 | 2.72 | 1040 | 1.1559 | 0.6790 | 0.6421 | 0.6454 | 0.6421 |
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| 0.4414 | 2.74 | 1050 | 1.1359 | 0.6839 | 0.6507 | 0.6537 | 0.6507 |
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| 0.295 | 2.77 | 1060 | 1.1392 | 0.6871 | 0.6533 | 0.6564 | 0.6533 |
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| 0.3978 | 2.79 | 1070 | 1.1553 | 0.6883 | 0.6516 | 0.6537 | 0.6516 |
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| 0.3656 | 2.82 | 1080 | 1.1505 | 0.6865 | 0.6473 | 0.6504 | 0.6473 |
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| 0.4054 | 2.85 | 1090 | 1.1605 | 0.6866 | 0.6429 | 0.6468 | 0.6429 |
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| 0.2833 | 2.87 | 1100 | 1.1673 | 0.6804 | 0.6386 | 0.6398 | 0.6386 |
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| 0.4412 | 2.9 | 1110 | 1.1555 | 0.6815 | 0.6438 | 0.6457 | 0.6438 |
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| 0.3246 | 2.92 | 1120 | 1.1437 | 0.6844 | 0.6533 | 0.6549 | 0.6533 |
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| 0.3567 | 2.95 | 1130 | 1.1374 | 0.6834 | 0.6542 | 0.6564 | 0.6542 |
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| 0.2376 | 2.98 | 1140 | 1.1385 | 0.6820 | 0.6507 | 0.6533 | 0.6507 |
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### Framework versions
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- Transformers 4.35.2
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- Pytorch 2.1.0+cu121
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- Tokenizers 0.15.1
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---
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license: mit
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base_model: xlm-roberta-large
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tags:
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- generated_from_trainer
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model-index:
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- name: results
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results: []
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# results
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This model is a fine-tuned version of [xlm-roberta-large](https://huggingface.co/xlm-roberta-large) on the None dataset.
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It achieves the following results on the evaluation set:
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- eval_loss: 1.9243
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- eval_accuracy: 0.1677
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- eval_f1: 0.0482
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- eval_precision: 0.0281
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- eval_recall: 0.1677
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- eval_runtime: 27.8461
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- eval_samples_per_second: 41.334
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- eval_steps_per_second: 10.343
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- epoch: 2.0
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- step: 3064
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## Model description
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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: 4
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- eval_batch_size: 4
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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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- lr_scheduler_warmup_steps: 500
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- num_epochs: 3
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| 55 |
### Framework versions
|
| 56 |
|
| 57 |
- Transformers 4.35.2
|
| 58 |
- Pytorch 2.1.0+cu121
|
| 59 |
+
- Datasets 2.16.1
|
| 60 |
- Tokenizers 0.15.1
|
config.json
CHANGED
|
@@ -1,13 +1,15 @@
|
|
| 1 |
{
|
| 2 |
-
"_name_or_path": "
|
| 3 |
"architectures": [
|
| 4 |
-
"
|
| 5 |
],
|
| 6 |
"attention_probs_dropout_prob": 0.1,
|
|
|
|
| 7 |
"classifier_dropout": null,
|
|
|
|
| 8 |
"hidden_act": "gelu",
|
| 9 |
"hidden_dropout_prob": 0.1,
|
| 10 |
-
"hidden_size":
|
| 11 |
"id2label": {
|
| 12 |
"0": "LABEL_0",
|
| 13 |
"1": "LABEL_1",
|
|
@@ -18,7 +20,7 @@
|
|
| 18 |
"6": "LABEL_6"
|
| 19 |
},
|
| 20 |
"initializer_range": 0.02,
|
| 21 |
-
"intermediate_size":
|
| 22 |
"label2id": {
|
| 23 |
"LABEL_0": 0,
|
| 24 |
"LABEL_1": 1,
|
|
@@ -28,17 +30,18 @@
|
|
| 28 |
"LABEL_5": 5,
|
| 29 |
"LABEL_6": 6
|
| 30 |
},
|
| 31 |
-
"layer_norm_eps": 1e-
|
| 32 |
-
"max_position_embeddings":
|
| 33 |
-
"model_type": "
|
| 34 |
-
"num_attention_heads":
|
| 35 |
-
"num_hidden_layers":
|
| 36 |
-
"
|
|
|
|
| 37 |
"position_embedding_type": "absolute",
|
| 38 |
"problem_type": "single_label_classification",
|
| 39 |
"torch_dtype": "float32",
|
| 40 |
"transformers_version": "4.35.2",
|
| 41 |
-
"type_vocab_size":
|
| 42 |
"use_cache": true,
|
| 43 |
-
"vocab_size":
|
| 44 |
}
|
|
|
|
| 1 |
{
|
| 2 |
+
"_name_or_path": "xlm-roberta-large",
|
| 3 |
"architectures": [
|
| 4 |
+
"XLMRobertaForSequenceClassification"
|
| 5 |
],
|
| 6 |
"attention_probs_dropout_prob": 0.1,
|
| 7 |
+
"bos_token_id": 0,
|
| 8 |
"classifier_dropout": null,
|
| 9 |
+
"eos_token_id": 2,
|
| 10 |
"hidden_act": "gelu",
|
| 11 |
"hidden_dropout_prob": 0.1,
|
| 12 |
+
"hidden_size": 1024,
|
| 13 |
"id2label": {
|
| 14 |
"0": "LABEL_0",
|
| 15 |
"1": "LABEL_1",
|
|
|
|
| 20 |
"6": "LABEL_6"
|
| 21 |
},
|
| 22 |
"initializer_range": 0.02,
|
| 23 |
+
"intermediate_size": 4096,
|
| 24 |
"label2id": {
|
| 25 |
"LABEL_0": 0,
|
| 26 |
"LABEL_1": 1,
|
|
|
|
| 30 |
"LABEL_5": 5,
|
| 31 |
"LABEL_6": 6
|
| 32 |
},
|
| 33 |
+
"layer_norm_eps": 1e-05,
|
| 34 |
+
"max_position_embeddings": 514,
|
| 35 |
+
"model_type": "xlm-roberta",
|
| 36 |
+
"num_attention_heads": 16,
|
| 37 |
+
"num_hidden_layers": 24,
|
| 38 |
+
"output_past": true,
|
| 39 |
+
"pad_token_id": 1,
|
| 40 |
"position_embedding_type": "absolute",
|
| 41 |
"problem_type": "single_label_classification",
|
| 42 |
"torch_dtype": "float32",
|
| 43 |
"transformers_version": "4.35.2",
|
| 44 |
+
"type_vocab_size": 1,
|
| 45 |
"use_cache": true,
|
| 46 |
+
"vocab_size": 250002
|
| 47 |
}
|
model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
-
size
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:4f0da9d08689af171e267e59a4a4b5375f38b7630dc6978135069b68d1beaf49
|
| 3 |
+
size 2239639172
|
training_args.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 4536
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:ec3f71c5c4db4193ad92eac8a5a8e834cca67cf36cd38e78a969b13079bdec65
|
| 3 |
size 4536
|