Commit
•
f2e976c
1
Parent(s):
849fe90
Evaluation on the test set completed on 2024_09_18.
Browse files- README.md +147 -0
- all_results.json +18 -0
- logs/events.out.tfevents.1726594904.datavisu4 +2 -2
- logs/events.out.tfevents.1726619814.datavisu4 +3 -0
- model.safetensors +1 -1
- test_results.json +13 -0
- train_results.json +9 -0
- trainer_state.json +1438 -0
README.md
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---
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license: apache-2.0
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base_model: facebook/dinov2-large
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tags:
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- generated_from_trainer
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model-index:
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- name: drone-DinoVdeau-large-2024_09_17-batch-size64_epochs100_freeze
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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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# drone-DinoVdeau-large-2024_09_17-batch-size64_epochs100_freeze
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This model is a fine-tuned version of [facebook/dinov2-large](https://huggingface.co/facebook/dinov2-large) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.3578
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- Mse: 0.0378
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- Rmse: 0.1943
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- Mae: 0.1288
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- R2: 0.4008
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- Explained Variance: 0.4014
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- Learning Rate: 0.0000
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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: 0.001
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- train_batch_size: 64
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- eval_batch_size: 64
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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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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Mse | Rmse | Mae | R2 | Explained Variance | Rate |
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|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:------:|:------------------:|:------:|
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| No log | 1.0 | 181 | 0.3858 | 0.0464 | 0.2153 | 0.1571 | 0.2624 | 0.2805 | 0.001 |
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| 57 |
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| No log | 2.0 | 362 | 0.3764 | 0.0440 | 0.2097 | 0.1467 | 0.3121 | 0.3209 | 0.001 |
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| 0.4473 | 3.0 | 543 | 0.3716 | 0.0425 | 0.2062 | 0.1450 | 0.3319 | 0.3394 | 0.001 |
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| 0.4473 | 4.0 | 724 | 0.3673 | 0.0410 | 0.2024 | 0.1395 | 0.3548 | 0.3566 | 0.001 |
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| 0.4473 | 5.0 | 905 | 0.3692 | 0.0419 | 0.2046 | 0.1393 | 0.3425 | 0.3494 | 0.001 |
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| 0.3892 | 6.0 | 1086 | 0.3673 | 0.0409 | 0.2022 | 0.1412 | 0.3554 | 0.3590 | 0.001 |
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| 0.3892 | 7.0 | 1267 | 0.3681 | 0.0415 | 0.2038 | 0.1408 | 0.3457 | 0.3499 | 0.001 |
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| 0.3892 | 8.0 | 1448 | 0.3656 | 0.0406 | 0.2015 | 0.1389 | 0.3596 | 0.3642 | 0.001 |
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| 0.3855 | 9.0 | 1629 | 0.3659 | 0.0408 | 0.2019 | 0.1344 | 0.3555 | 0.3613 | 0.001 |
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| 0.3855 | 10.0 | 1810 | 0.3666 | 0.0409 | 0.2023 | 0.1384 | 0.3533 | 0.3562 | 0.001 |
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| 0.3855 | 11.0 | 1991 | 0.3666 | 0.0409 | 0.2022 | 0.1366 | 0.3550 | 0.3574 | 0.001 |
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| 0.3816 | 12.0 | 2172 | 0.3663 | 0.0409 | 0.2021 | 0.1396 | 0.3587 | 0.3598 | 0.001 |
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| 0.3816 | 13.0 | 2353 | 0.3632 | 0.0398 | 0.1995 | 0.1361 | 0.3697 | 0.3705 | 0.001 |
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| 0.381 | 14.0 | 2534 | 0.3669 | 0.0410 | 0.2024 | 0.1423 | 0.3562 | 0.3628 | 0.001 |
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| 0.381 | 15.0 | 2715 | 0.3645 | 0.0404 | 0.2009 | 0.1395 | 0.3620 | 0.3645 | 0.001 |
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| 0.381 | 16.0 | 2896 | 0.3639 | 0.0400 | 0.2000 | 0.1357 | 0.3695 | 0.3715 | 0.001 |
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| 0.3811 | 17.0 | 3077 | 0.3667 | 0.0406 | 0.2016 | 0.1413 | 0.3622 | 0.3728 | 0.001 |
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| 0.3811 | 18.0 | 3258 | 0.3632 | 0.0398 | 0.1995 | 0.1368 | 0.3695 | 0.3705 | 0.001 |
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| 0.3811 | 19.0 | 3439 | 0.3630 | 0.0397 | 0.1994 | 0.1354 | 0.3719 | 0.3734 | 0.001 |
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| 0.3792 | 20.0 | 3620 | 0.3649 | 0.0405 | 0.2013 | 0.1349 | 0.3587 | 0.3622 | 0.001 |
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| 0.3792 | 21.0 | 3801 | 0.3665 | 0.0407 | 0.2017 | 0.1361 | 0.3585 | 0.3631 | 0.001 |
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| 0.3792 | 22.0 | 3982 | 0.3648 | 0.0400 | 0.2000 | 0.1369 | 0.3678 | 0.3705 | 0.001 |
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| 0.3808 | 23.0 | 4163 | 0.3633 | 0.0398 | 0.1996 | 0.1356 | 0.3705 | 0.3736 | 0.001 |
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| 0.3808 | 24.0 | 4344 | 0.3632 | 0.0397 | 0.1991 | 0.1393 | 0.3725 | 0.3761 | 0.001 |
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| 0.3796 | 25.0 | 4525 | 0.3638 | 0.0399 | 0.1997 | 0.1381 | 0.3698 | 0.3734 | 0.001 |
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| 0.3796 | 26.0 | 4706 | 0.3607 | 0.0390 | 0.1975 | 0.1329 | 0.3818 | 0.3836 | 0.0001 |
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| 0.3796 | 27.0 | 4887 | 0.3600 | 0.0387 | 0.1967 | 0.1353 | 0.3863 | 0.3878 | 0.0001 |
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| 0.3765 | 28.0 | 5068 | 0.3592 | 0.0384 | 0.1961 | 0.1337 | 0.3894 | 0.3904 | 0.0001 |
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| 0.3765 | 29.0 | 5249 | 0.3595 | 0.0385 | 0.1961 | 0.1350 | 0.3892 | 0.3915 | 0.0001 |
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| 0.3765 | 30.0 | 5430 | 0.3598 | 0.0386 | 0.1965 | 0.1350 | 0.3876 | 0.3893 | 0.0001 |
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| 0.373 | 31.0 | 5611 | 0.3587 | 0.0384 | 0.1959 | 0.1317 | 0.3907 | 0.3921 | 0.0001 |
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| 0.373 | 32.0 | 5792 | 0.3584 | 0.0383 | 0.1956 | 0.1326 | 0.3928 | 0.3932 | 0.0001 |
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| 0.373 | 33.0 | 5973 | 0.3581 | 0.0381 | 0.1953 | 0.1311 | 0.3945 | 0.3953 | 0.0001 |
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| 0.3735 | 34.0 | 6154 | 0.3580 | 0.0381 | 0.1951 | 0.1323 | 0.3953 | 0.3967 | 0.0001 |
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| 0.3735 | 35.0 | 6335 | 0.3579 | 0.0381 | 0.1951 | 0.1322 | 0.3949 | 0.3954 | 0.0001 |
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| 0.3711 | 36.0 | 6516 | 0.3592 | 0.0385 | 0.1963 | 0.1345 | 0.3895 | 0.3899 | 0.0001 |
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| 0.3711 | 37.0 | 6697 | 0.3575 | 0.0380 | 0.1949 | 0.1313 | 0.3966 | 0.3970 | 0.0001 |
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| 0.3711 | 38.0 | 6878 | 0.3582 | 0.0383 | 0.1956 | 0.1326 | 0.3923 | 0.3936 | 0.0001 |
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| 0.3705 | 39.0 | 7059 | 0.3576 | 0.0380 | 0.1948 | 0.1313 | 0.3963 | 0.3965 | 0.0001 |
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| 0.3705 | 40.0 | 7240 | 0.3575 | 0.0379 | 0.1947 | 0.1333 | 0.3980 | 0.4000 | 0.0001 |
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| 0.3705 | 41.0 | 7421 | 0.3580 | 0.0381 | 0.1952 | 0.1317 | 0.3956 | 0.3988 | 0.0001 |
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| 0.3704 | 42.0 | 7602 | 0.3575 | 0.0380 | 0.1949 | 0.1330 | 0.3970 | 0.3986 | 0.0001 |
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| 0.3704 | 43.0 | 7783 | 0.3569 | 0.0377 | 0.1942 | 0.1325 | 0.4008 | 0.4020 | 0.0001 |
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| 0.3704 | 44.0 | 7964 | 0.3568 | 0.0377 | 0.1942 | 0.1305 | 0.4009 | 0.4026 | 0.0001 |
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| 0.3695 | 45.0 | 8145 | 0.3567 | 0.0376 | 0.1940 | 0.1319 | 0.4021 | 0.4033 | 0.0001 |
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| 0.3695 | 46.0 | 8326 | 0.3569 | 0.0377 | 0.1943 | 0.1298 | 0.3998 | 0.4015 | 0.0001 |
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| 0.369 | 47.0 | 8507 | 0.3574 | 0.0380 | 0.1948 | 0.1292 | 0.3973 | 0.3996 | 0.0001 |
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| 0.369 | 48.0 | 8688 | 0.3563 | 0.0376 | 0.1940 | 0.1302 | 0.4019 | 0.4041 | 0.0001 |
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| 0.369 | 49.0 | 8869 | 0.3566 | 0.0377 | 0.1940 | 0.1306 | 0.4011 | 0.4024 | 0.0001 |
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| 0.3691 | 50.0 | 9050 | 0.3571 | 0.0378 | 0.1944 | 0.1322 | 0.3998 | 0.4015 | 0.0001 |
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| 0.3691 | 51.0 | 9231 | 0.3584 | 0.0381 | 0.1952 | 0.1335 | 0.3958 | 0.4021 | 0.0001 |
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| 0.3691 | 52.0 | 9412 | 0.3561 | 0.0375 | 0.1936 | 0.1309 | 0.4042 | 0.4045 | 0.0001 |
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| 0.3677 | 53.0 | 9593 | 0.3565 | 0.0376 | 0.1939 | 0.1315 | 0.4026 | 0.4053 | 0.0001 |
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| 0.3677 | 54.0 | 9774 | 0.3567 | 0.0377 | 0.1943 | 0.1316 | 0.4011 | 0.4018 | 0.0001 |
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| 0.3677 | 55.0 | 9955 | 0.3565 | 0.0376 | 0.1939 | 0.1292 | 0.4026 | 0.4052 | 0.0001 |
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| 0.3684 | 56.0 | 10136 | 0.3567 | 0.0377 | 0.1941 | 0.1279 | 0.4017 | 0.4046 | 0.0001 |
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| 0.3684 | 57.0 | 10317 | 0.3562 | 0.0376 | 0.1938 | 0.1294 | 0.4032 | 0.4049 | 0.0001 |
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| 0.3684 | 58.0 | 10498 | 0.3565 | 0.0376 | 0.1938 | 0.1299 | 0.4036 | 0.4062 | 0.0001 |
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| 0.368 | 59.0 | 10679 | 0.3559 | 0.0375 | 0.1936 | 0.1292 | 0.4047 | 0.4061 | 1e-05 |
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| 0.368 | 60.0 | 10860 | 0.3559 | 0.0374 | 0.1934 | 0.1295 | 0.4060 | 0.4082 | 1e-05 |
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| 0.3664 | 61.0 | 11041 | 0.3555 | 0.0373 | 0.1932 | 0.1304 | 0.4072 | 0.4075 | 1e-05 |
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| 0.3664 | 62.0 | 11222 | 0.3565 | 0.0376 | 0.1939 | 0.1317 | 0.4036 | 0.4058 | 1e-05 |
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| 0.3664 | 63.0 | 11403 | 0.3556 | 0.0373 | 0.1930 | 0.1293 | 0.4075 | 0.4087 | 1e-05 |
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| 0.366 | 64.0 | 11584 | 0.3554 | 0.0373 | 0.1931 | 0.1296 | 0.4077 | 0.4089 | 1e-05 |
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| 0.366 | 65.0 | 11765 | 0.3560 | 0.0375 | 0.1938 | 0.1307 | 0.4049 | 0.4059 | 1e-05 |
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| 0.366 | 66.0 | 11946 | 0.3553 | 0.0372 | 0.1930 | 0.1300 | 0.4080 | 0.4085 | 1e-05 |
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| 0.3654 | 67.0 | 12127 | 0.3554 | 0.0373 | 0.1930 | 0.1299 | 0.4078 | 0.4082 | 1e-05 |
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| 0.3654 | 68.0 | 12308 | 0.3556 | 0.0374 | 0.1934 | 0.1302 | 0.4059 | 0.4074 | 1e-05 |
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| 0.3654 | 69.0 | 12489 | 0.3554 | 0.0373 | 0.1930 | 0.1298 | 0.4083 | 0.4086 | 1e-05 |
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| 0.3658 | 70.0 | 12670 | 0.3559 | 0.0374 | 0.1933 | 0.1307 | 0.4066 | 0.4094 | 1e-05 |
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| 0.3658 | 71.0 | 12851 | 0.3557 | 0.0374 | 0.1933 | 0.1296 | 0.4070 | 0.4073 | 1e-05 |
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| 127 |
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| 0.366 | 72.0 | 13032 | 0.3557 | 0.0373 | 0.1932 | 0.1303 | 0.4070 | 0.4084 | 1e-05 |
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| 128 |
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| 0.366 | 73.0 | 13213 | 0.3552 | 0.0372 | 0.1929 | 0.1299 | 0.4082 | 0.4090 | 0.0000 |
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| 0.366 | 74.0 | 13394 | 0.3552 | 0.0372 | 0.1929 | 0.1281 | 0.4087 | 0.4094 | 0.0000 |
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| 0.3654 | 75.0 | 13575 | 0.3558 | 0.0375 | 0.1936 | 0.1303 | 0.4047 | 0.4057 | 0.0000 |
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| 0.3654 | 76.0 | 13756 | 0.3555 | 0.0374 | 0.1933 | 0.1277 | 0.4061 | 0.4084 | 0.0000 |
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| 132 |
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| 0.3654 | 77.0 | 13937 | 0.3562 | 0.0376 | 0.1938 | 0.1321 | 0.4042 | 0.4046 | 0.0000 |
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| 133 |
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| 0.3663 | 78.0 | 14118 | 0.3553 | 0.0372 | 0.1929 | 0.1306 | 0.4087 | 0.4090 | 0.0000 |
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| 0.3663 | 79.0 | 14299 | 0.3569 | 0.0379 | 0.1947 | 0.1310 | 0.3999 | 0.4020 | 0.0000 |
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| 0.3663 | 80.0 | 14480 | 0.3563 | 0.0375 | 0.1936 | 0.1311 | 0.4052 | 0.4058 | 0.0000 |
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| 0.3655 | 81.0 | 14661 | 0.3555 | 0.0373 | 0.1930 | 0.1308 | 0.4079 | 0.4092 | 0.0000 |
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| 0.3655 | 82.0 | 14842 | 0.3556 | 0.0373 | 0.1932 | 0.1309 | 0.4072 | 0.4087 | 0.0000 |
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| 0.3651 | 83.0 | 15023 | 0.3557 | 0.0373 | 0.1932 | 0.1304 | 0.4074 | 0.4102 | 0.0000 |
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| 0.3651 | 84.0 | 15204 | 0.3558 | 0.0374 | 0.1934 | 0.1306 | 0.4063 | 0.4082 | 0.0000 |
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### Framework versions
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- Transformers 4.41.1
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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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all_results.json
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{
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"epoch": 84.0,
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"eval_explained_variance": 0.40141621002784145,
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"eval_loss": 0.35779908299446106,
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"eval_mae": 0.12878435850143433,
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"eval_mse": 0.0377507321536541,
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"eval_r2": 0.4007782891079936,
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"eval_rmse": 0.1942954808473587,
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"eval_runtime": 66.1225,
|
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|
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|
| 17 |
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|
| 18 |
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|
logs/events.out.tfevents.1726594904.datavisu4
CHANGED
|
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size 61604
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ADDED
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model.safetensors
CHANGED
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@@ -1,3 +1,3 @@
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|
| 1 |
version https://git-lfs.github.com/spec/v1
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| 2 |
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test_results.json
ADDED
|
@@ -0,0 +1,13 @@
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|
| 1 |
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{
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|
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|
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|
| 12 |
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"learning_rate": 1.0000000000000002e-07
|
| 13 |
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}
|
train_results.json
ADDED
|
@@ -0,0 +1,9 @@
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|
| 8 |
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"train_steps_per_second": 0.734
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| 9 |
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|
trainer_state.json
ADDED
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@@ -0,0 +1,1438 @@
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