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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: google/flan-t5-large |
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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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model-index: |
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- name: flanT5_large_Fact_U |
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results: [] |
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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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# flanT5_large_Fact_U |
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This model is a fine-tuned version of [google/flan-t5-large](https://huggingface.co./google/flan-t5-large) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Accuracy: 0.7812 |
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- F1 score: 0.7842 |
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- Precision: 0.8048 |
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- Recall: 0.7647 |
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- Loss: 1.5959 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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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: 0.0001 |
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- train_batch_size: 1 |
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- eval_batch_size: 1 |
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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: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Accuracy | F1 score | Precision | Recall | Validation Loss | |
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|:-------------:|:------:|:-----:|:--------:|:--------:|:---------:|:------:|:---------------:| |
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| 1.2434 | 0.0314 | 200 | 0.6059 | 0.6974 | 0.5805 | 0.8733 | 0.7545 | |
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| 1.4323 | 0.0628 | 400 | 0.6 | 0.6970 | 0.575 | 0.8846 | 1.7199 | |
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| 1.253 | 0.0941 | 600 | 0.6059 | 0.6957 | 0.5812 | 0.8665 | 1.3828 | |
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| 1.2986 | 0.1255 | 800 | 0.48 | 0.0 | 0.0 | 0.0 | 2.4072 | |
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| 1.2843 | 0.1569 | 1000 | 0.6553 | 0.5925 | 0.7690 | 0.4819 | 1.2474 | |
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| 1.2245 | 0.1883 | 1200 | 0.5435 | 0.2271 | 0.95 | 0.1290 | 1.3841 | |
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| 1.2389 | 0.2197 | 1400 | 0.6706 | 0.6923 | 0.6731 | 0.7127 | 0.8993 | |
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| 1.132 | 0.2511 | 1600 | 0.6271 | 0.6846 | 0.6110 | 0.7783 | 0.6845 | |
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| 1.0836 | 0.2824 | 1800 | 0.6824 | 0.6574 | 0.7486 | 0.5860 | 1.1694 | |
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| 1.2434 | 0.3138 | 2000 | 0.6788 | 0.6422 | 0.7632 | 0.5543 | 1.4787 | |
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| 1.1196 | 0.3452 | 2200 | 0.6694 | 0.6659 | 0.7018 | 0.6335 | 1.5004 | |
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| 1.5791 | 0.3766 | 2400 | 0.6376 | 0.5157 | 0.8454 | 0.3710 | 1.1289 | |
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| 1.3035 | 0.4080 | 2600 | 0.6859 | 0.6877 | 0.7119 | 0.6652 | 1.0136 | |
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| 1.1401 | 0.4394 | 2800 | 0.6753 | 0.6443 | 0.7485 | 0.5656 | 1.2340 | |
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| 0.9518 | 0.4707 | 3000 | 0.7024 | 0.6810 | 0.7692 | 0.6109 | 1.2197 | |
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| 1.1623 | 0.5021 | 3200 | 0.6788 | 0.6807 | 0.7046 | 0.6584 | 1.2827 | |
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| 1.1316 | 0.5335 | 3400 | 0.6659 | 0.7183 | 0.6396 | 0.8190 | 1.5077 | |
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| 1.2599 | 0.5649 | 3600 | 0.6341 | 0.5071 | 0.8466 | 0.3620 | 0.8272 | |
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| 0.9866 | 0.5963 | 3800 | 0.6647 | 0.6939 | 0.6605 | 0.7308 | 1.4574 | |
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| 1.147 | 0.6276 | 4000 | 0.6824 | 0.64 | 0.7792 | 0.5430 | 1.2933 | |
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| 1.0307 | 0.6590 | 4200 | 0.6482 | 0.5795 | 0.7658 | 0.4661 | 1.1586 | |
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| 1.0616 | 0.6904 | 4400 | 0.6976 | 0.6877 | 0.7428 | 0.6403 | 1.2668 | |
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| 1.0724 | 0.7218 | 4600 | 0.6447 | 0.6225 | 0.6955 | 0.5633 | 1.1130 | |
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| 0.9499 | 0.7532 | 4800 | 0.7188 | 0.7046 | 0.7766 | 0.6448 | 1.1635 | |
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| 1.1302 | 0.7846 | 5000 | 0.7118 | 0.7357 | 0.7031 | 0.7715 | 1.2608 | |
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| 1.1921 | 0.8159 | 5200 | 0.7094 | 0.6754 | 0.8056 | 0.5814 | 1.1742 | |
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| 0.9532 | 0.8473 | 5400 | 0.7071 | 0.6860 | 0.7749 | 0.6154 | 1.1589 | |
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| 0.783 | 0.8787 | 5600 | 0.7 | 0.6577 | 0.8086 | 0.5543 | 1.3256 | |
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| 0.9835 | 0.9101 | 5800 | 0.7282 | 0.7166 | 0.7828 | 0.6606 | 1.1383 | |
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| 0.9898 | 0.9415 | 6000 | 0.7141 | 0.7158 | 0.7409 | 0.6923 | 1.0662 | |
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| 0.9768 | 0.9729 | 6200 | 0.7059 | 0.6711 | 0.8019 | 0.5769 | 1.1941 | |
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| 1.043 | 1.0042 | 6400 | 0.6729 | 0.5838 | 0.8628 | 0.4412 | 1.2302 | |
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| 0.9531 | 1.0356 | 6600 | 0.7106 | 0.7 | 0.7593 | 0.6493 | 1.1304 | |
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| 1.0585 | 1.0670 | 6800 | 0.7294 | 0.7132 | 0.7944 | 0.6471 | 1.0234 | |
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| 0.8862 | 1.0984 | 7000 | 0.6953 | 0.6230 | 0.8735 | 0.4842 | 1.1941 | |
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| 0.8721 | 1.1298 | 7200 | 0.7376 | 0.7271 | 0.792 | 0.6719 | 0.9352 | |
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| 0.8678 | 1.1611 | 7400 | 0.7388 | 0.7533 | 0.7402 | 0.7670 | 1.0473 | |
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| 0.7617 | 1.1925 | 7600 | 0.7294 | 0.7522 | 0.7181 | 0.7896 | 1.3020 | |
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| 1.0394 | 1.2239 | 7800 | 0.7212 | 0.7019 | 0.7904 | 0.6312 | 1.0322 | |
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| 0.822 | 1.2553 | 8000 | 0.7388 | 0.7266 | 0.7973 | 0.6674 | 1.0980 | |
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| 0.8406 | 1.2867 | 8200 | 0.7118 | 0.7357 | 0.7031 | 0.7715 | 1.4589 | |
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| 0.7059 | 1.3181 | 8400 | 0.7306 | 0.6999 | 0.8318 | 0.6041 | 1.0655 | |
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| 0.8649 | 1.3494 | 8600 | 0.7424 | 0.7266 | 0.8106 | 0.6584 | 0.9708 | |
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| 0.7142 | 1.3808 | 8800 | 0.7553 | 0.7419 | 0.8214 | 0.6765 | 1.1603 | |
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| 0.9057 | 1.4122 | 9000 | 0.76 | 0.7431 | 0.8381 | 0.6674 | 0.9389 | |
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| 0.9312 | 1.4436 | 9200 | 0.7553 | 0.7615 | 0.7721 | 0.7511 | 1.0568 | |
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| 0.8459 | 1.4750 | 9400 | 0.7459 | 0.7372 | 0.7974 | 0.6855 | 1.1646 | |
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| 0.8427 | 1.5064 | 9600 | 0.7459 | 0.7293 | 0.8174 | 0.6584 | 1.0133 | |
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| 0.7245 | 1.5377 | 9800 | 0.7341 | 0.6861 | 0.8885 | 0.5588 | 1.1397 | |
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| 0.6386 | 1.5691 | 10000 | 0.7294 | 0.6742 | 0.9015 | 0.5385 | 1.1112 | |
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| 0.7513 | 1.6005 | 10200 | 0.7671 | 0.7648 | 0.805 | 0.7285 | 0.9403 | |
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| 0.828 | 1.6319 | 10400 | 0.76 | 0.7639 | 0.7820 | 0.7466 | 0.9412 | |
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| 0.8393 | 1.6633 | 10600 | 0.7553 | 0.7219 | 0.8824 | 0.6109 | 0.9359 | |
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| 0.8679 | 1.6946 | 10800 | 0.7588 | 0.7402 | 0.8415 | 0.6606 | 0.8979 | |
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| 0.6735 | 1.7260 | 11000 | 0.7588 | 0.7285 | 0.8786 | 0.6222 | 1.0666 | |
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| 0.8702 | 1.7574 | 11200 | 0.7576 | 0.7553 | 0.795 | 0.7195 | 0.9554 | |
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| 0.7435 | 1.7888 | 11400 | 0.7588 | 0.7497 | 0.8143 | 0.6946 | 1.0937 | |
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| 0.8796 | 1.8202 | 11600 | 0.7824 | 0.7768 | 0.8320 | 0.7285 | 0.9257 | |
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| 0.6257 | 1.8516 | 11800 | 0.7659 | 0.7588 | 0.8172 | 0.7081 | 0.9606 | |
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| 0.8589 | 1.8829 | 12000 | 0.7659 | 0.7484 | 0.8481 | 0.6697 | 0.9013 | |
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| 0.865 | 1.9143 | 12200 | 0.7612 | 0.7717 | 0.7673 | 0.7760 | 1.0734 | |
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| 0.8068 | 1.9457 | 12400 | 0.76 | 0.7431 | 0.8381 | 0.6674 | 0.9214 | |
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| 0.6212 | 1.9771 | 12600 | 0.7706 | 0.7535 | 0.8539 | 0.6742 | 1.0116 | |
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| 0.7657 | 2.0085 | 12800 | 0.7718 | 0.7532 | 0.8605 | 0.6697 | 0.9830 | |
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| 0.6631 | 2.0399 | 13000 | 0.7776 | 0.7810 | 0.8005 | 0.7624 | 1.0075 | |
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| 0.3003 | 2.0712 | 13200 | 0.7812 | 0.7748 | 0.8333 | 0.7240 | 1.1456 | |
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| 0.5982 | 2.1026 | 13400 | 0.7753 | 0.7633 | 0.8438 | 0.6968 | 1.0728 | |
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| 0.4828 | 2.1340 | 13600 | 0.7753 | 0.7718 | 0.8177 | 0.7308 | 1.0474 | |
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| 0.5463 | 2.1654 | 13800 | 0.7776 | 0.7726 | 0.8252 | 0.7262 | 1.0521 | |
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| 0.5429 | 2.1968 | 14000 | 0.7706 | 0.7590 | 0.8365 | 0.6946 | 1.0990 | |
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| 0.7112 | 2.2282 | 14200 | 0.7729 | 0.7578 | 0.8507 | 0.6833 | 1.1072 | |
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| 0.4816 | 2.2595 | 14400 | 0.7753 | 0.7685 | 0.8277 | 0.7172 | 1.1528 | |
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| 0.7882 | 2.2909 | 14600 | 0.7765 | 0.7722 | 0.8214 | 0.7285 | 0.9670 | |
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| 0.5265 | 2.3223 | 14800 | 0.7765 | 0.7694 | 0.8298 | 0.7172 | 1.0724 | |
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| 0.6116 | 2.3537 | 15000 | 0.7776 | 0.7742 | 0.8203 | 0.7330 | 1.0316 | |
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| 0.575 | 2.3851 | 15200 | 0.7741 | 0.7624 | 0.8415 | 0.6968 | 1.1125 | |
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| 0.5599 | 2.4164 | 15400 | 0.7765 | 0.7754 | 0.8119 | 0.7421 | 1.0327 | |
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| 0.5821 | 2.4478 | 15600 | 0.7776 | 0.7784 | 0.8078 | 0.7511 | 1.0655 | |
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| 0.4777 | 2.4792 | 15800 | 0.7835 | 0.7880 | 0.8028 | 0.7738 | 1.1187 | |
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| 0.432 | 2.5106 | 16000 | 0.7788 | 0.7740 | 0.8256 | 0.7285 | 1.1973 | |
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| 0.4385 | 2.5420 | 16200 | 0.7729 | 0.7737 | 0.8029 | 0.7466 | 1.2155 | |
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| 0.6103 | 2.5734 | 16400 | 0.78 | 0.7771 | 0.8212 | 0.7376 | 1.0527 | |
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| 0.4618 | 2.6047 | 16600 | 0.78 | 0.7787 | 0.8164 | 0.7443 | 1.1377 | |
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| 0.471 | 2.6361 | 16800 | 0.7788 | 0.7814 | 0.8038 | 0.7602 | 1.1468 | |
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| 0.6206 | 2.6675 | 17000 | 0.7765 | 0.7791 | 0.8014 | 0.7579 | 1.1048 | |
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| 0.5869 | 2.6989 | 17200 | 0.7776 | 0.7850 | 0.7895 | 0.7805 | 1.1343 | |
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| 0.5647 | 2.7303 | 17400 | 0.7859 | 0.7849 | 0.8218 | 0.7511 | 1.0843 | |
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| 0.5527 | 2.7617 | 17600 | 0.7847 | 0.7875 | 0.8091 | 0.7670 | 1.0834 | |
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| 0.8013 | 2.7930 | 17800 | 0.7894 | 0.7926 | 0.8124 | 0.7738 | 0.9898 | |
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| 0.5232 | 2.8244 | 18000 | 0.7859 | 0.7884 | 0.8110 | 0.7670 | 1.0052 | |
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| 0.617 | 2.8558 | 18200 | 0.7824 | 0.7821 | 0.8157 | 0.7511 | 1.0083 | |
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| 0.5093 | 2.8872 | 18400 | 0.7835 | 0.7810 | 0.8241 | 0.7421 | 1.0510 | |
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| 0.5099 | 2.9186 | 18600 | 0.78 | 0.7797 | 0.8133 | 0.7489 | 1.0758 | |
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| 0.6239 | 2.9499 | 18800 | 0.7812 | 0.7801 | 0.8168 | 0.7466 | 1.0726 | |
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| 0.6592 | 2.9813 | 19000 | 0.7788 | 0.7773 | 0.8159 | 0.7421 | 1.0731 | |
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| 0.1354 | 3.0127 | 19200 | 0.7765 | 0.7791 | 0.8014 | 0.7579 | 1.3351 | |
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| 0.3893 | 3.0755 | 19600 | 0.7835 | 0.7933 | 0.7879 | 0.7986 | 1.1745 | |
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| 0.4753 | 3.1382 | 20000 | 0.7882 | 0.7783 | 0.8541 | 0.7149 | 1.2362 | |
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| 0.3696 | 3.2010 | 20400 | 0.7847 | 0.7850 | 0.8166 | 0.7557 | 1.2638 | |
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| 0.4476 | 3.2638 | 20800 | 0.7706 | 0.7522 | 0.8580 | 0.6697 | 1.3415 | |
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| 0.4819 | 3.3265 | 21200 | 0.7776 | 0.7731 | 0.8235 | 0.7285 | 1.2743 | |
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| 0.4361 | 3.3893 | 21600 | 0.7765 | 0.7727 | 0.8198 | 0.7308 | 1.1387 | |
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| 0.3522 | 3.4521 | 22000 | 0.7694 | 0.7773 | 0.7808 | 0.7738 | 1.4823 | |
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| 0.4655 | 3.5148 | 22400 | 0.7529 | 0.7789 | 0.7283 | 0.8371 | 1.4060 | |
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| 0.438 | 3.5776 | 22800 | 0.7659 | 0.7651 | 0.8 | 0.7330 | 1.2310 | |
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| 0.5766 | 3.6404 | 23200 | 0.7776 | 0.7869 | 0.7843 | 0.7896 | 1.2406 | |
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| 0.5009 | 3.7031 | 23600 | 0.7882 | 0.7950 | 0.8005 | 0.7896 | 1.1521 | |
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| 0.4282 | 3.7659 | 24000 | 0.7765 | 0.7860 | 0.7825 | 0.7896 | 1.2111 | |
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| 0.3733 | 3.8287 | 24400 | 0.7765 | 0.7780 | 0.8043 | 0.7534 | 1.3162 | |
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| 0.5248 | 3.8914 | 24800 | 0.7788 | 0.7814 | 0.8038 | 0.7602 | 1.2680 | |
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| 0.4236 | 3.9542 | 25200 | 0.7706 | 0.7802 | 0.7775 | 0.7828 | 1.3282 | |
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| 0.5013 | 4.0169 | 25600 | 0.7753 | 0.7792 | 0.7967 | 0.7624 | 1.2586 | |
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| 0.2414 | 4.0797 | 26000 | 0.7741 | 0.7773 | 0.7976 | 0.7579 | 1.2782 | |
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| 0.1564 | 4.1425 | 26400 | 0.78 | 0.7797 | 0.8133 | 0.7489 | 1.4687 | |
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| 0.2116 | 4.2052 | 26800 | 0.7694 | 0.7768 | 0.7821 | 0.7715 | 1.3950 | |
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| 0.288 | 4.2680 | 27200 | 0.7753 | 0.7766 | 0.8039 | 0.7511 | 1.3878 | |
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| 0.1134 | 4.3308 | 27600 | 0.7729 | 0.7721 | 0.8074 | 0.7398 | 1.6678 | |
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| 0.1839 | 4.3935 | 28000 | 0.7729 | 0.7705 | 0.8120 | 0.7330 | 1.6949 | |
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| 0.1831 | 4.4563 | 28400 | 0.78 | 0.7808 | 0.8102 | 0.7534 | 1.5547 | |
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| 0.2417 | 4.5191 | 28800 | 0.7847 | 0.7824 | 0.8246 | 0.7443 | 1.4637 | |
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| 0.1922 | 4.5818 | 29200 | 0.7824 | 0.7821 | 0.8157 | 0.7511 | 1.5513 | |
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| 0.252 | 4.6446 | 29600 | 0.78 | 0.7808 | 0.8102 | 0.7534 | 1.5873 | |
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| 0.2172 | 4.7074 | 30000 | 0.7882 | 0.7867 | 0.8259 | 0.7511 | 1.5172 | |
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| 0.1177 | 4.7701 | 30400 | 0.7824 | 0.7866 | 0.8024 | 0.7715 | 1.5945 | |
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| 0.1921 | 4.8329 | 30800 | 0.7812 | 0.7842 | 0.8048 | 0.7647 | 1.6031 | |
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| 0.1833 | 4.8957 | 31200 | 0.7765 | 0.7831 | 0.7903 | 0.7760 | 1.5854 | |
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| 0.243 | 4.9584 | 31600 | 0.7812 | 0.7842 | 0.8048 | 0.7647 | 1.5959 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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