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README.md
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| 1 |
+
---
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| 2 |
+
library_name: transformers
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| 3 |
+
license: cc-by-nc-4.0
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| 4 |
+
base_model: MCG-NJU/videomae-large-finetuned-kinetics
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| 5 |
+
tags:
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| 6 |
+
- generated_from_trainer
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| 7 |
+
metrics:
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| 8 |
+
- accuracy
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| 9 |
+
model-index:
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| 10 |
+
- name: MAE-CT-M1N0-M12_v8_split3_v3
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| 11 |
+
results: []
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| 12 |
+
---
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| 13 |
+
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| 14 |
+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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| 15 |
+
should probably proofread and complete it, then remove this comment. -->
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| 16 |
+
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| 17 |
+
# MAE-CT-M1N0-M12_v8_split3_v3
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+
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+
This model is a fine-tuned version of [MCG-NJU/videomae-large-finetuned-kinetics](https://huggingface.co/MCG-NJU/videomae-large-finetuned-kinetics) on an unknown dataset.
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| 20 |
+
It achieves the following results on the evaluation set:
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| 21 |
+
- Loss: 1.0548
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| 22 |
+
- Accuracy: 0.8462
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| 23 |
+
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| 24 |
+
## Model description
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| 25 |
+
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| 26 |
+
More information needed
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| 27 |
+
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## Intended uses & limitations
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| 29 |
+
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| 30 |
+
More information needed
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| 31 |
+
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| 32 |
+
## Training and evaluation data
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| 33 |
+
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| 34 |
+
More information needed
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| 35 |
+
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| 36 |
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## Training procedure
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| 37 |
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### Training hyperparameters
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| 39 |
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The following hyperparameters were used during training:
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| 41 |
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- learning_rate: 1e-05
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| 42 |
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- train_batch_size: 4
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| 43 |
+
- eval_batch_size: 4
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| 44 |
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- seed: 42
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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| 46 |
+
- lr_scheduler_type: linear
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| 47 |
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- lr_scheduler_warmup_ratio: 0.1
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| 48 |
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- training_steps: 10350
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| 49 |
+
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| 50 |
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### Training results
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| 51 |
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| 52 |
+
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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| 53 |
+
|:-------------:|:--------:|:-----:|:---------------:|:--------:|
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| 54 |
+
| 0.6676 | 0.0068 | 70 | 0.6765 | 0.6538 |
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| 55 |
+
| 0.6735 | 1.0068 | 140 | 0.6379 | 0.6667 |
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| 56 |
+
| 0.6391 | 2.0068 | 210 | 0.6261 | 0.6667 |
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| 57 |
+
| 0.8085 | 3.0068 | 280 | 0.6050 | 0.6667 |
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| 58 |
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| 0.4774 | 4.0068 | 350 | 0.5725 | 0.6538 |
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| 59 |
+
| 0.5668 | 5.0068 | 420 | 0.5514 | 0.7179 |
|
| 60 |
+
| 0.6607 | 6.0068 | 490 | 0.4834 | 0.7564 |
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| 61 |
+
| 1.0769 | 7.0068 | 560 | 0.7450 | 0.6667 |
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| 62 |
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| 0.5425 | 8.0068 | 630 | 0.4623 | 0.7949 |
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| 63 |
+
| 0.2959 | 9.0068 | 700 | 0.5113 | 0.7564 |
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| 64 |
+
| 0.7674 | 10.0068 | 770 | 0.5330 | 0.7308 |
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| 65 |
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| 0.3015 | 11.0068 | 840 | 0.6790 | 0.7436 |
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| 66 |
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| 0.6252 | 12.0068 | 910 | 1.6537 | 0.6667 |
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| 67 |
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| 0.4554 | 13.0068 | 980 | 0.8944 | 0.7564 |
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| 68 |
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| 0.364 | 14.0068 | 1050 | 0.8103 | 0.7179 |
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| 69 |
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| 0.444 | 15.0068 | 1120 | 0.7103 | 0.7821 |
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| 70 |
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| 0.104 | 16.0068 | 1190 | 0.9000 | 0.7179 |
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| 71 |
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| 0.5647 | 17.0068 | 1260 | 1.4782 | 0.7051 |
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| 72 |
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| 0.783 | 18.0068 | 1330 | 0.8539 | 0.8205 |
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| 73 |
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| 0.5938 | 19.0068 | 1400 | 0.8426 | 0.7564 |
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| 74 |
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| 0.5341 | 20.0068 | 1470 | 0.9862 | 0.7949 |
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| 75 |
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| 0.3391 | 21.0068 | 1540 | 1.1159 | 0.7692 |
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| 76 |
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| 0.2071 | 22.0068 | 1610 | 1.5833 | 0.7692 |
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| 77 |
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| 0.1159 | 23.0068 | 1680 | 1.0205 | 0.8205 |
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| 78 |
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| 0.1579 | 24.0068 | 1750 | 1.4633 | 0.7692 |
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| 79 |
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| 0.1042 | 25.0068 | 1820 | 1.5864 | 0.7564 |
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| 80 |
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| 0.1466 | 26.0068 | 1890 | 1.2990 | 0.7692 |
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| 81 |
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| 0.0006 | 27.0068 | 1960 | 1.5597 | 0.7564 |
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| 82 |
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| 0.001 | 28.0068 | 2030 | 1.6434 | 0.7564 |
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| 83 |
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| 0.0096 | 29.0068 | 2100 | 1.4161 | 0.7821 |
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| 84 |
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| 0.0015 | 30.0068 | 2170 | 1.3385 | 0.7949 |
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| 85 |
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| 0.3627 | 31.0068 | 2240 | 1.7864 | 0.7436 |
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| 86 |
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| 0.1541 | 32.0068 | 2310 | 1.5618 | 0.7821 |
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| 87 |
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| 0.1285 | 33.0068 | 2380 | 1.3062 | 0.7949 |
|
| 88 |
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| 0.2193 | 34.0068 | 2450 | 1.5554 | 0.7821 |
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| 89 |
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| 0.0002 | 35.0068 | 2520 | 1.5445 | 0.7949 |
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| 90 |
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| 0.0003 | 36.0068 | 2590 | 1.7189 | 0.7821 |
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| 91 |
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| 0.092 | 37.0068 | 2660 | 1.4980 | 0.7692 |
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| 92 |
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| 0.2403 | 38.0068 | 2730 | 2.0993 | 0.7436 |
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| 93 |
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| 0.0001 | 39.0068 | 2800 | 1.8646 | 0.7436 |
|
| 94 |
+
| 0.0001 | 40.0068 | 2870 | 1.6642 | 0.7436 |
|
| 95 |
+
| 0.2108 | 41.0068 | 2940 | 1.4566 | 0.7949 |
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| 96 |
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| 0.1085 | 42.0068 | 3010 | 1.2915 | 0.7821 |
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| 97 |
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| 0.0019 | 43.0068 | 3080 | 1.2691 | 0.8333 |
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| 98 |
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| 0.0072 | 44.0068 | 3150 | 2.2703 | 0.7179 |
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| 99 |
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| 0.0002 | 45.0068 | 3220 | 1.5151 | 0.7564 |
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| 100 |
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| 0.4057 | 46.0068 | 3290 | 1.4170 | 0.7564 |
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| 101 |
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| 0.0862 | 47.0068 | 3360 | 2.1072 | 0.7308 |
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| 102 |
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| 0.0478 | 48.0068 | 3430 | 1.6826 | 0.7949 |
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| 103 |
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| 0.001 | 49.0068 | 3500 | 1.4349 | 0.7564 |
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| 104 |
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| 0.0001 | 50.0068 | 3570 | 1.4423 | 0.7949 |
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| 105 |
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| 0.0056 | 51.0068 | 3640 | 2.2833 | 0.7051 |
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| 106 |
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| 0.0004 | 52.0068 | 3710 | 1.0548 | 0.8462 |
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| 107 |
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| 0.1768 | 53.0068 | 3780 | 1.2974 | 0.8077 |
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| 108 |
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| 0.0001 | 54.0068 | 3850 | 1.2797 | 0.8333 |
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| 109 |
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| 0.1027 | 55.0068 | 3920 | 1.5159 | 0.8077 |
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| 110 |
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| 0.1638 | 56.0068 | 3990 | 1.9403 | 0.7564 |
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| 111 |
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| 0.0001 | 57.0068 | 4060 | 1.5075 | 0.8077 |
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| 112 |
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| 0.0003 | 58.0068 | 4130 | 2.1291 | 0.7436 |
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| 113 |
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| 0.004 | 59.0068 | 4200 | 1.6104 | 0.7949 |
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| 114 |
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| 0.0214 | 60.0068 | 4270 | 1.7017 | 0.7949 |
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| 115 |
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| 0.0 | 61.0068 | 4340 | 1.6485 | 0.8205 |
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| 116 |
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| 0.0 | 62.0068 | 4410 | 1.6668 | 0.8077 |
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| 117 |
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| 0.1604 | 63.0068 | 4480 | 1.7437 | 0.7949 |
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| 118 |
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| 0.0002 | 64.0068 | 4550 | 1.6770 | 0.7821 |
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| 119 |
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| 0.0 | 65.0068 | 4620 | 1.7766 | 0.7821 |
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| 120 |
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| 0.0214 | 66.0068 | 4690 | 1.6351 | 0.7821 |
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| 121 |
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| 0.0 | 67.0068 | 4760 | 1.6878 | 0.7821 |
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| 122 |
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| 0.0 | 68.0068 | 4830 | 1.8764 | 0.7564 |
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| 123 |
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| 0.2082 | 69.0068 | 4900 | 1.7799 | 0.7564 |
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| 124 |
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| 0.0 | 70.0068 | 4970 | 1.7388 | 0.7949 |
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| 125 |
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| 0.0 | 71.0068 | 5040 | 1.6719 | 0.7949 |
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| 126 |
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| 0.0001 | 72.0068 | 5110 | 1.6066 | 0.7949 |
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| 127 |
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| 0.0001 | 73.0068 | 5180 | 2.1181 | 0.7564 |
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| 128 |
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| 0.0 | 74.0068 | 5250 | 2.1773 | 0.7564 |
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| 129 |
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| 0.0 | 75.0068 | 5320 | 2.5632 | 0.7179 |
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| 130 |
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| 0.0 | 76.0068 | 5390 | 1.1549 | 0.8077 |
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| 131 |
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| 0.0006 | 77.0068 | 5460 | 2.2296 | 0.7436 |
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| 132 |
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| 0.0 | 78.0068 | 5530 | 2.5382 | 0.7308 |
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| 133 |
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| 0.0001 | 79.0068 | 5600 | 1.5726 | 0.7821 |
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| 0.0002 | 80.0068 | 5670 | 1.5704 | 0.8077 |
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| 135 |
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| 0.0199 | 81.0068 | 5740 | 1.5503 | 0.8077 |
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| 0.0001 | 82.0068 | 5810 | 1.3654 | 0.8077 |
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| 0.0 | 83.0068 | 5880 | 1.4727 | 0.8077 |
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| 0.0001 | 84.0068 | 5950 | 2.2248 | 0.7179 |
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| 139 |
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| 0.0 | 85.0068 | 6020 | 1.7188 | 0.7821 |
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| 140 |
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| 0.0101 | 86.0068 | 6090 | 1.9271 | 0.7436 |
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| 141 |
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| 0.0001 | 87.0068 | 6160 | 1.5356 | 0.8333 |
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| 142 |
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| 0.0 | 88.0068 | 6230 | 1.6683 | 0.8077 |
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| 143 |
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| 0.0 | 89.0068 | 6300 | 2.5566 | 0.7308 |
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| 144 |
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| 0.0 | 90.0068 | 6370 | 1.7776 | 0.8077 |
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| 145 |
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| 0.0028 | 91.0068 | 6440 | 1.7494 | 0.7949 |
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| 146 |
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| 0.0 | 92.0068 | 6510 | 1.6141 | 0.8077 |
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| 147 |
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| 0.0 | 93.0068 | 6580 | 2.8243 | 0.7179 |
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| 148 |
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| 0.0 | 94.0068 | 6650 | 1.9026 | 0.7051 |
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| 149 |
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| 0.0002 | 95.0068 | 6720 | 2.2368 | 0.6667 |
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| 150 |
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| 0.0998 | 96.0068 | 6790 | 2.4985 | 0.7179 |
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| 151 |
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| 0.0 | 97.0068 | 6860 | 2.0686 | 0.7436 |
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| 152 |
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| 0.0074 | 98.0068 | 6930 | 2.7098 | 0.7051 |
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| 153 |
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| 0.0 | 99.0068 | 7000 | 2.2765 | 0.7308 |
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| 154 |
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| 0.0 | 100.0068 | 7070 | 2.2793 | 0.7308 |
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| 155 |
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| 0.0 | 101.0068 | 7140 | 2.2027 | 0.7308 |
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| 156 |
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| 0.0 | 102.0068 | 7210 | 2.2387 | 0.7308 |
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| 157 |
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| 0.0 | 103.0068 | 7280 | 2.1971 | 0.7308 |
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| 158 |
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| 0.0 | 104.0068 | 7350 | 2.3246 | 0.7179 |
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| 159 |
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| 0.0 | 105.0068 | 7420 | 1.5935 | 0.8077 |
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| 0.0 | 106.0068 | 7490 | 1.4796 | 0.8077 |
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| 161 |
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| 0.0001 | 107.0068 | 7560 | 1.7052 | 0.7821 |
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| 162 |
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| 0.0 | 108.0068 | 7630 | 1.6022 | 0.8077 |
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| 163 |
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| 0.0002 | 109.0068 | 7700 | 1.6749 | 0.8077 |
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| 164 |
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| 0.0 | 110.0068 | 7770 | 1.7948 | 0.7436 |
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| 165 |
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| 0.0 | 111.0068 | 7840 | 1.8455 | 0.7949 |
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| 166 |
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| 0.0 | 112.0068 | 7910 | 1.8600 | 0.7949 |
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| 167 |
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| 0.0 | 113.0068 | 7980 | 1.8183 | 0.7949 |
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| 168 |
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| 0.0 | 114.0068 | 8050 | 1.7862 | 0.7949 |
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| 169 |
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| 0.0 | 115.0068 | 8120 | 1.8597 | 0.7821 |
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| 170 |
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| 0.0 | 116.0068 | 8190 | 1.8203 | 0.7821 |
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| 171 |
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| 0.0 | 117.0068 | 8260 | 1.8343 | 0.7949 |
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| 0.0 | 118.0068 | 8330 | 1.8417 | 0.7949 |
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| 173 |
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| 0.0 | 119.0068 | 8400 | 1.7663 | 0.7821 |
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| 174 |
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| 0.0 | 120.0068 | 8470 | 1.9611 | 0.7821 |
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| 0.0 | 121.0068 | 8540 | 1.9584 | 0.7949 |
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| 0.0 | 122.0068 | 8610 | 1.5671 | 0.8205 |
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| 0.0 | 123.0068 | 8680 | 2.3456 | 0.7564 |
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| 0.0 | 124.0068 | 8750 | 2.3453 | 0.7564 |
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| 0.0 | 125.0068 | 8820 | 2.4120 | 0.7436 |
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| 0.0 | 126.0068 | 8890 | 2.3774 | 0.7436 |
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| 0.0 | 127.0068 | 8960 | 2.3609 | 0.7436 |
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| 0.0 | 128.0068 | 9030 | 2.3531 | 0.7564 |
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| 0.0 | 129.0068 | 9100 | 1.9910 | 0.7821 |
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| 0.0 | 130.0068 | 9170 | 2.0032 | 0.7821 |
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| 0.0 | 131.0068 | 9240 | 2.0645 | 0.7692 |
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| 0.0 | 132.0068 | 9310 | 2.0598 | 0.7692 |
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| 0.0 | 133.0068 | 9380 | 2.0594 | 0.7692 |
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| 0.0 | 134.0068 | 9450 | 2.0568 | 0.7692 |
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| 0.0 | 135.0068 | 9520 | 2.0522 | 0.7821 |
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| 0.0 | 136.0068 | 9590 | 1.9971 | 0.7564 |
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| 0.0 | 137.0068 | 9660 | 1.9977 | 0.7564 |
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| 0.0 | 138.0068 | 9730 | 2.0896 | 0.7692 |
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| 0.0 | 139.0068 | 9800 | 2.1550 | 0.7692 |
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| 0.0 | 140.0068 | 9870 | 2.1875 | 0.7692 |
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| 195 |
+
| 0.0 | 141.0068 | 9940 | 2.1874 | 0.7692 |
|
| 196 |
+
| 0.0 | 142.0068 | 10010 | 2.1822 | 0.7692 |
|
| 197 |
+
| 0.0 | 143.0068 | 10080 | 2.1818 | 0.7692 |
|
| 198 |
+
| 0.0 | 144.0068 | 10150 | 2.1806 | 0.7692 |
|
| 199 |
+
| 0.0 | 145.0068 | 10220 | 2.1803 | 0.7692 |
|
| 200 |
+
| 0.0 | 146.0068 | 10290 | 2.1804 | 0.7692 |
|
| 201 |
+
| 0.0 | 147.0058 | 10350 | 2.1803 | 0.7692 |
|
| 202 |
+
|
| 203 |
+
|
| 204 |
+
### Framework versions
|
| 205 |
+
|
| 206 |
+
- Transformers 4.46.2
|
| 207 |
+
- Pytorch 2.0.1+cu117
|
| 208 |
+
- Datasets 3.0.1
|
| 209 |
+
- Tokenizers 0.20.0
|
model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 1215496208
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:3069c194e2b6dd0e4587e021333a4b340c794095dc7abbb16a789fbb5a7a2dea
|
| 3 |
size 1215496208
|