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mt5-small-finetuned-mt5

Text2Text Generation
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mt5
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  1. .gitattributes +1 -0
  2. README.md +162 -0
  3. config.json +32 -0
  4. generation_config.json +6 -0
  5. model.safetensors +3 -0
  6. runs/Feb23_06-43-14_58f3319be355/events.out.tfevents.1708670697.58f3319be355.5247.0 +3 -0
  7. runs/Feb23_06-43-14_58f3319be355/events.out.tfevents.1708670764.58f3319be355.5247.1 +3 -0
  8. runs/Feb23_06-47-47_58f3319be355/events.out.tfevents.1708670870.58f3319be355.5247.2 +3 -0
  9. special_tokens_map.json +23 -0
  10. spiece.model +3 -0
  11. tokenizer.json +3 -0
  12. tokenizer_config.json +38 -0
  13. 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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  *tfevents* 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
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+ ---
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+ license: apache-2.0
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+ base_model: google/mt5-small
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - rouge
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+ model-index:
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+ - name: mt5-small-finetuned-mt5
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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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+ # mt5-small-finetuned-mt5
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+
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+ This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.6691
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+ - Rouge1: 0.5388
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+ - Rouge2: 0.3838
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+ - Rougel: 0.5283
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+ - Rougelsum: 0.5270
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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: 5.6e-05
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+ - train_batch_size: 20
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+ - eval_batch_size: 20
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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: 100
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
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+ | 12.893 | 1.0 | 8 | 7.2101 | 0.0967 | 0.0309 | 0.0928 | 0.0928 |
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+ | 12.4326 | 2.0 | 16 | 6.0616 | 0.1183 | 0.0458 | 0.1140 | 0.1141 |
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+ | 12.0044 | 3.0 | 24 | 5.5399 | 0.1239 | 0.0469 | 0.1212 | 0.1200 |
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+ | 11.4794 | 4.0 | 32 | 5.2619 | 0.1504 | 0.0541 | 0.1450 | 0.1470 |
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+ | 10.85 | 5.0 | 40 | 4.8356 | 0.1675 | 0.0574 | 0.1605 | 0.1626 |
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+ | 10.2044 | 6.0 | 48 | 4.2656 | 0.1933 | 0.0746 | 0.1862 | 0.1905 |
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+ | 9.2904 | 7.0 | 56 | 3.7518 | 0.1983 | 0.0787 | 0.1891 | 0.1921 |
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+ | 8.7029 | 8.0 | 64 | 3.4376 | 0.1873 | 0.0698 | 0.1797 | 0.1818 |
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+ | 8.3889 | 9.0 | 72 | 3.2085 | 0.1811 | 0.0672 | 0.1738 | 0.1771 |
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+ | 7.5091 | 10.0 | 80 | 3.0059 | 0.1581 | 0.0581 | 0.1557 | 0.1564 |
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+ | 7.2132 | 11.0 | 88 | 2.8329 | 0.1654 | 0.0466 | 0.1623 | 0.1616 |
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+ | 6.796 | 12.0 | 96 | 2.6879 | 0.1735 | 0.0486 | 0.1620 | 0.1617 |
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+ | 6.4213 | 13.0 | 104 | 2.5694 | 0.1799 | 0.0482 | 0.1722 | 0.1726 |
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+ | 5.7867 | 14.0 | 112 | 2.4405 | 0.1776 | 0.0497 | 0.1720 | 0.1715 |
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+ | 5.2668 | 15.0 | 120 | 2.3098 | 0.1860 | 0.0521 | 0.1759 | 0.1766 |
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+ | 5.0803 | 16.0 | 128 | 2.1944 | 0.2010 | 0.0677 | 0.1931 | 0.1939 |
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+ | 4.6867 | 17.0 | 136 | 2.1139 | 0.2179 | 0.0811 | 0.2114 | 0.2117 |
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+ | 4.5557 | 18.0 | 144 | 2.0466 | 0.2186 | 0.0805 | 0.2099 | 0.2103 |
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+ | 4.4414 | 19.0 | 152 | 1.9919 | 0.2260 | 0.0916 | 0.2177 | 0.2172 |
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+ | 4.0867 | 20.0 | 160 | 1.9404 | 0.2317 | 0.0976 | 0.2228 | 0.2221 |
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+ | 3.6814 | 21.0 | 168 | 1.9014 | 0.2287 | 0.0921 | 0.2170 | 0.2157 |
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+ | 3.5426 | 22.0 | 176 | 1.8656 | 0.2208 | 0.0862 | 0.2139 | 0.2131 |
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+ | 3.266 | 23.0 | 184 | 1.8224 | 0.2348 | 0.0935 | 0.2232 | 0.2224 |
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+ | 3.32 | 24.0 | 192 | 1.7907 | 0.2443 | 0.1072 | 0.2355 | 0.2348 |
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+ | 3.1872 | 25.0 | 200 | 1.7459 | 0.2563 | 0.1121 | 0.2421 | 0.2414 |
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+ | 2.9643 | 26.0 | 208 | 1.7043 | 0.2703 | 0.1213 | 0.2598 | 0.2591 |
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+ | 2.8918 | 27.0 | 216 | 1.6654 | 0.2755 | 0.1190 | 0.2633 | 0.2634 |
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+ | 2.7626 | 28.0 | 224 | 1.6199 | 0.3008 | 0.1385 | 0.2870 | 0.2861 |
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+ | 2.8192 | 29.0 | 232 | 1.5712 | 0.3061 | 0.1410 | 0.2948 | 0.2942 |
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+ | 2.5082 | 30.0 | 240 | 1.5405 | 0.3161 | 0.1533 | 0.3073 | 0.3069 |
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+ | 2.564 | 31.0 | 248 | 1.5111 | 0.3296 | 0.1662 | 0.3198 | 0.3196 |
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+ | 2.5577 | 32.0 | 256 | 1.4738 | 0.3344 | 0.1745 | 0.3250 | 0.3247 |
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+ | 2.5199 | 33.0 | 264 | 1.4378 | 0.3468 | 0.1829 | 0.3336 | 0.3328 |
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+ | 2.4798 | 34.0 | 272 | 1.4033 | 0.3593 | 0.1969 | 0.3448 | 0.3450 |
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+ | 2.3208 | 35.0 | 280 | 1.3733 | 0.3728 | 0.2146 | 0.3613 | 0.3609 |
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+ | 2.3704 | 36.0 | 288 | 1.3403 | 0.3721 | 0.2175 | 0.3644 | 0.3649 |
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+ | 2.3199 | 37.0 | 296 | 1.3092 | 0.3718 | 0.2147 | 0.3638 | 0.3631 |
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+ | 2.3046 | 38.0 | 304 | 1.2838 | 0.3674 | 0.2141 | 0.3608 | 0.3610 |
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+ | 2.3183 | 39.0 | 312 | 1.2599 | 0.3728 | 0.2202 | 0.3664 | 0.3669 |
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+ | 2.178 | 40.0 | 320 | 1.2272 | 0.3826 | 0.2274 | 0.3758 | 0.3749 |
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+ | 2.1264 | 41.0 | 328 | 1.1940 | 0.3923 | 0.2348 | 0.3841 | 0.3835 |
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+ | 2.0563 | 42.0 | 336 | 1.1629 | 0.3972 | 0.2391 | 0.3864 | 0.3865 |
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+ | 2.0213 | 43.0 | 344 | 1.1324 | 0.4082 | 0.2509 | 0.3981 | 0.3980 |
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+ | 1.9956 | 44.0 | 352 | 1.1085 | 0.4158 | 0.2569 | 0.4051 | 0.4054 |
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+ | 2.0723 | 45.0 | 360 | 1.0895 | 0.4186 | 0.2594 | 0.4060 | 0.4061 |
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+ | 1.9021 | 46.0 | 368 | 1.0713 | 0.4316 | 0.2775 | 0.4193 | 0.4194 |
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+ | 1.9776 | 47.0 | 376 | 1.0510 | 0.4362 | 0.2785 | 0.4232 | 0.4237 |
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+ | 1.8752 | 48.0 | 384 | 1.0289 | 0.4371 | 0.2778 | 0.4225 | 0.4230 |
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+ | 1.8729 | 49.0 | 392 | 1.0070 | 0.4386 | 0.2766 | 0.4243 | 0.4245 |
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+ | 1.6512 | 57.0 | 456 | 0.9015 | 0.4803 | 0.3201 | 0.4699 | 0.4691 |
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+ | 1.6403 | 66.0 | 528 | 0.8064 | 0.4983 | 0.3419 | 0.4867 | 0.4862 |
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+ | 1.6281 | 67.0 | 536 | 0.7955 | 0.4992 | 0.3426 | 0.4866 | 0.4866 |
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+ | 1.6482 | 68.0 | 544 | 0.7881 | 0.4990 | 0.3404 | 0.4860 | 0.4860 |
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+ | 1.6103 | 69.0 | 552 | 0.7822 | 0.4997 | 0.3401 | 0.4882 | 0.4872 |
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+ | 1.5396 | 70.0 | 560 | 0.7769 | 0.5023 | 0.3411 | 0.4896 | 0.4890 |
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+ | 1.5271 | 71.0 | 568 | 0.7696 | 0.5040 | 0.3396 | 0.4908 | 0.4899 |
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+ | 1.4252 | 72.0 | 576 | 0.7614 | 0.5128 | 0.3521 | 0.4999 | 0.4994 |
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+ | 1.553 | 73.0 | 584 | 0.7541 | 0.5145 | 0.3525 | 0.5017 | 0.5012 |
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+ | 1.5503 | 74.0 | 592 | 0.7475 | 0.5193 | 0.3561 | 0.5052 | 0.5047 |
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+ | 1.4653 | 75.0 | 600 | 0.7415 | 0.5151 | 0.3540 | 0.5020 | 0.5018 |
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+ | 1.5387 | 76.0 | 608 | 0.7355 | 0.5267 | 0.3632 | 0.5126 | 0.5121 |
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+ | 1.5706 | 77.0 | 616 | 0.7292 | 0.5232 | 0.3628 | 0.5101 | 0.5096 |
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+ | 1.4442 | 78.0 | 624 | 0.7229 | 0.5208 | 0.3626 | 0.5086 | 0.5082 |
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+ | 1.4816 | 79.0 | 632 | 0.7173 | 0.5193 | 0.3606 | 0.5070 | 0.5060 |
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+ | 1.5228 | 80.0 | 640 | 0.7119 | 0.5180 | 0.3596 | 0.5057 | 0.5053 |
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+ | 1.4191 | 84.0 | 672 | 0.6934 | 0.5307 | 0.3732 | 0.5200 | 0.5192 |
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+ | 1.4564 | 85.0 | 680 | 0.6898 | 0.5317 | 0.3764 | 0.5213 | 0.5202 |
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+ | 1.4195 | 86.0 | 688 | 0.6872 | 0.5311 | 0.3751 | 0.5203 | 0.5186 |
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+ | 1.4213 | 100.0 | 800 | 0.6691 | 0.5388 | 0.3838 | 0.5283 | 0.5270 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.37.2
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+ - Pytorch 2.1.0+cu121
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+ - Datasets 2.17.1
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+ - Tokenizers 0.15.2
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