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bert_baseline_prompt_adherence_task4_fold1

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  1. README.md +173 -39
  2. model.safetensors +1 -1
  3. runs/Aug22_10-22-58_0095ffe889f2/events.out.tfevents.1724322179.0095ffe889f2.25.0 +3 -0
  4. runs/Aug22_10-45-22_0095ffe889f2/events.out.tfevents.1724323523.0095ffe889f2.25.1 +3 -0
  5. runs/Aug22_11-07-47_0095ffe889f2/events.out.tfevents.1724324868.0095ffe889f2.25.2 +3 -0
  6. runs/Aug22_11-30-11_0095ffe889f2/events.out.tfevents.1724326212.0095ffe889f2.25.3 +3 -0
  7. runs/Aug22_11-52-37_0095ffe889f2/events.out.tfevents.1724327557.0095ffe889f2.25.4 +3 -0
  8. runs/Aug22_12-15-04_0095ffe889f2/events.out.tfevents.1724328905.0095ffe889f2.25.5 +3 -0
  9. runs/Aug22_12-38-55_0095ffe889f2/events.out.tfevents.1724330336.0095ffe889f2.25.6 +3 -0
  10. training_args.bin +1 -1
README.md CHANGED
@@ -4,20 +4,20 @@ base_model: google-bert/bert-base-cased
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  tags:
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  - generated_from_trainer
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  model-index:
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- - name: bert_baseline_prompt_adherence_task4_fold1
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  results: []
9
  ---
10
 
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
12
  should probably proofread and complete it, then remove this comment. -->
13
 
14
- # bert_baseline_prompt_adherence_task4_fold1
15
 
16
  This model is a fine-tuned version of [google-bert/bert-base-cased](https://huggingface.co/google-bert/bert-base-cased) on the None dataset.
17
  It achieves the following results on the evaluation set:
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- - Loss: 0.3776
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- - Qwk: 0.6594
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- - Mse: 0.3794
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  ## Model description
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@@ -42,45 +42,179 @@ The following hyperparameters were used during training:
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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: 1
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Qwk | Mse |
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  |:-------------:|:------:|:----:|:---------------:|:------:|:------:|
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- | No log | 0.0299 | 2 | 2.2564 | 0.0 | 2.2575 |
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- | No log | 0.0597 | 4 | 1.6809 | 0.0 | 1.6816 |
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- | No log | 0.0896 | 6 | 1.0910 | 0.0 | 1.0910 |
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- | No log | 0.1194 | 8 | 0.7512 | 0.2651 | 0.7511 |
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- | No log | 0.1493 | 10 | 0.6255 | 0.3428 | 0.6255 |
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- | No log | 0.1791 | 12 | 0.5553 | 0.3646 | 0.5554 |
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- | No log | 0.2090 | 14 | 0.5086 | 0.3601 | 0.5089 |
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- | No log | 0.2388 | 16 | 0.5178 | 0.3566 | 0.5186 |
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- | No log | 0.2687 | 18 | 0.4479 | 0.4269 | 0.4487 |
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- | No log | 0.2985 | 20 | 0.4166 | 0.4397 | 0.4172 |
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- | No log | 0.3284 | 22 | 0.4894 | 0.3973 | 0.4896 |
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- | No log | 0.3582 | 24 | 0.4800 | 0.4089 | 0.4803 |
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- | No log | 0.3881 | 26 | 0.4100 | 0.4996 | 0.4107 |
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- | No log | 0.4179 | 28 | 0.4060 | 0.5607 | 0.4074 |
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- | No log | 0.4478 | 30 | 0.4137 | 0.5350 | 0.4151 |
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- | No log | 0.4776 | 32 | 0.4050 | 0.5391 | 0.4063 |
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- | No log | 0.5075 | 34 | 0.4049 | 0.5581 | 0.4063 |
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- | No log | 0.5373 | 36 | 0.4067 | 0.5113 | 0.4078 |
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- | No log | 0.5672 | 38 | 0.4015 | 0.5240 | 0.4026 |
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- | No log | 0.5970 | 40 | 0.3886 | 0.5907 | 0.3900 |
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- | No log | 0.6269 | 42 | 0.3885 | 0.6312 | 0.3902 |
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- | No log | 0.6567 | 44 | 0.3907 | 0.6442 | 0.3925 |
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- | No log | 0.6866 | 46 | 0.3806 | 0.6424 | 0.3822 |
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- | No log | 0.7164 | 48 | 0.3733 | 0.6378 | 0.3747 |
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- | No log | 0.7463 | 50 | 0.3688 | 0.6029 | 0.3700 |
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- | No log | 0.7761 | 52 | 0.3637 | 0.6021 | 0.3649 |
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- | No log | 0.8060 | 54 | 0.3610 | 0.6445 | 0.3623 |
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- | No log | 0.8358 | 56 | 0.3617 | 0.6492 | 0.3631 |
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- | No log | 0.8657 | 58 | 0.3610 | 0.6441 | 0.3625 |
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- | No log | 0.8955 | 60 | 0.3702 | 0.6499 | 0.3718 |
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- | No log | 0.9254 | 62 | 0.3774 | 0.6599 | 0.3791 |
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- | No log | 0.9552 | 64 | 0.3767 | 0.6599 | 0.3784 |
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- | No log | 0.9851 | 66 | 0.3776 | 0.6594 | 0.3794 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
84
 
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  ### Framework versions
 
4
  tags:
5
  - generated_from_trainer
6
  model-index:
7
+ - name: bert_baseline_prompt_adherence_task4_fold0
8
  results: []
9
  ---
10
 
11
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
12
  should probably proofread and complete it, then remove this comment. -->
13
 
14
+ # bert_baseline_prompt_adherence_task4_fold0
15
 
16
  This model is a fine-tuned version of [google-bert/bert-base-cased](https://huggingface.co/google-bert/bert-base-cased) on the None dataset.
17
  It achieves the following results on the evaluation set:
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+ - Loss: 0.3287
19
+ - Qwk: 0.7248
20
+ - Mse: 0.3247
21
 
22
  ## Model description
23
 
 
42
  - seed: 42
43
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
44
  - lr_scheduler_type: linear
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+ - num_epochs: 5
46
 
47
  ### Training results
48
 
49
  | Training Loss | Epoch | Step | Validation Loss | Qwk | Mse |
50
  |:-------------:|:------:|:----:|:---------------:|:------:|:------:|
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+ | No log | 0.0299 | 2 | 0.9346 | 0.0 | 0.9328 |
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+ | No log | 0.0597 | 4 | 0.8762 | 0.3376 | 0.8746 |
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+ | No log | 0.0896 | 6 | 0.8267 | 0.3789 | 0.8251 |
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+ | No log | 0.1194 | 8 | 0.7675 | 0.3809 | 0.7660 |
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+ | No log | 0.1493 | 10 | 0.6965 | 0.3771 | 0.6951 |
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+ | No log | 0.1791 | 12 | 0.6230 | 0.3658 | 0.6217 |
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+ | No log | 0.2090 | 14 | 0.5320 | 0.3843 | 0.5292 |
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+ | No log | 0.2388 | 16 | 0.4894 | 0.4044 | 0.4858 |
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+ | No log | 0.2687 | 18 | 0.4757 | 0.4580 | 0.4718 |
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+ | No log | 0.2985 | 20 | 0.4704 | 0.5660 | 0.4665 |
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+ | No log | 0.3284 | 22 | 0.4632 | 0.5603 | 0.4594 |
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+ | No log | 0.3582 | 24 | 0.4791 | 0.6068 | 0.4754 |
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+ | No log | 0.3881 | 26 | 0.4743 | 0.5706 | 0.4708 |
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+ | No log | 0.4179 | 28 | 0.5106 | 0.4297 | 0.5071 |
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+ | No log | 0.4478 | 30 | 0.6764 | 0.2664 | 0.6729 |
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+ | No log | 0.4776 | 32 | 0.5556 | 0.3762 | 0.5522 |
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+ | No log | 0.5075 | 34 | 0.4133 | 0.5868 | 0.4101 |
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+ | No log | 0.5373 | 36 | 0.4757 | 0.6707 | 0.4729 |
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+ | No log | 0.5672 | 38 | 0.5453 | 0.6801 | 0.5429 |
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+ | No log | 0.5970 | 40 | 0.5164 | 0.7037 | 0.5139 |
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+ | No log | 0.6269 | 42 | 0.4243 | 0.6483 | 0.4214 |
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+ | No log | 0.6567 | 44 | 0.4446 | 0.4431 | 0.4413 |
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+ | No log | 0.6866 | 46 | 0.4980 | 0.3762 | 0.4944 |
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+ | No log | 0.7164 | 48 | 0.4330 | 0.4366 | 0.4294 |
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+ | No log | 0.7463 | 50 | 0.3883 | 0.6049 | 0.3849 |
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+ | No log | 0.7761 | 52 | 0.4350 | 0.6756 | 0.4320 |
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+ | No log | 0.8060 | 54 | 0.5041 | 0.6724 | 0.5014 |
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+ | No log | 0.8358 | 56 | 0.4888 | 0.6499 | 0.4858 |
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+ | No log | 0.8657 | 58 | 0.4641 | 0.5020 | 0.4606 |
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+ | No log | 0.8955 | 60 | 0.4165 | 0.5062 | 0.4124 |
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+ | No log | 0.9254 | 62 | 0.4079 | 0.4934 | 0.4035 |
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+ | No log | 0.9552 | 64 | 0.4116 | 0.4844 | 0.4072 |
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+ | No log | 0.9851 | 66 | 0.3856 | 0.5151 | 0.3814 |
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+ | No log | 1.0149 | 68 | 0.3717 | 0.6360 | 0.3680 |
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+ | No log | 1.0448 | 70 | 0.3834 | 0.6631 | 0.3802 |
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+ | No log | 1.0746 | 72 | 0.3956 | 0.6770 | 0.3930 |
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+ | No log | 1.1045 | 74 | 0.4079 | 0.6865 | 0.4056 |
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+ | No log | 1.1343 | 76 | 0.3904 | 0.6947 | 0.3878 |
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+ | No log | 1.1642 | 78 | 0.3679 | 0.6706 | 0.3648 |
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+ | No log | 1.1940 | 80 | 0.3543 | 0.6581 | 0.3506 |
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+ | No log | 1.2239 | 82 | 0.3671 | 0.5810 | 0.3629 |
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+ | No log | 1.2537 | 84 | 0.3737 | 0.5696 | 0.3694 |
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+ | No log | 1.2836 | 86 | 0.3454 | 0.6543 | 0.3412 |
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+ | No log | 1.3134 | 88 | 0.3739 | 0.7156 | 0.3701 |
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+ | No log | 1.3433 | 90 | 0.4277 | 0.7367 | 0.4246 |
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+ | No log | 1.3731 | 92 | 0.3952 | 0.7268 | 0.3919 |
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+ | No log | 1.4030 | 94 | 0.3791 | 0.7280 | 0.3759 |
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+ | No log | 1.4328 | 96 | 0.3518 | 0.7048 | 0.3485 |
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+ | No log | 1.4627 | 98 | 0.3241 | 0.6618 | 0.3202 |
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+ | No log | 1.4925 | 100 | 0.3180 | 0.6617 | 0.3138 |
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+ | No log | 1.5224 | 102 | 0.3201 | 0.6608 | 0.3158 |
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+ | No log | 1.5522 | 104 | 0.3189 | 0.6797 | 0.3147 |
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+ | No log | 1.5821 | 106 | 0.3211 | 0.7000 | 0.3171 |
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+ | No log | 1.6119 | 108 | 0.3240 | 0.7032 | 0.3202 |
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+ | No log | 1.6418 | 110 | 0.3182 | 0.6968 | 0.3144 |
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+ | No log | 1.6716 | 112 | 0.3193 | 0.6978 | 0.3155 |
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+ | No log | 1.7015 | 114 | 0.3208 | 0.6902 | 0.3170 |
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+ | No log | 1.7313 | 116 | 0.3205 | 0.6987 | 0.3168 |
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+ | No log | 1.7612 | 118 | 0.3217 | 0.6992 | 0.3180 |
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+ | No log | 1.7910 | 120 | 0.3304 | 0.7156 | 0.3270 |
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+ | No log | 1.8209 | 122 | 0.3171 | 0.7016 | 0.3136 |
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+ | No log | 1.8507 | 124 | 0.3119 | 0.6527 | 0.3084 |
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+ | No log | 1.8806 | 126 | 0.3146 | 0.6219 | 0.3111 |
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+ | No log | 1.9104 | 128 | 0.3155 | 0.6275 | 0.3121 |
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+ | No log | 1.9403 | 130 | 0.3193 | 0.6807 | 0.3163 |
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+ | No log | 1.9701 | 132 | 0.3256 | 0.6961 | 0.3225 |
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+ | No log | 2.0 | 134 | 0.3204 | 0.6759 | 0.3169 |
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+ | No log | 2.0299 | 136 | 0.3228 | 0.6927 | 0.3192 |
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+ | No log | 2.0597 | 138 | 0.3269 | 0.6914 | 0.3231 |
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+ | No log | 2.0896 | 140 | 0.3358 | 0.6980 | 0.3319 |
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+ | No log | 2.1194 | 142 | 0.3465 | 0.7191 | 0.3427 |
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+ | No log | 2.1493 | 144 | 0.3720 | 0.7386 | 0.3684 |
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+ | No log | 2.1791 | 146 | 0.3638 | 0.7394 | 0.3602 |
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+ | No log | 2.2090 | 148 | 0.3208 | 0.7083 | 0.3168 |
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+ | No log | 2.2388 | 150 | 0.3163 | 0.6588 | 0.3120 |
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+ | No log | 2.2687 | 152 | 0.3150 | 0.6519 | 0.3109 |
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+ | No log | 2.2985 | 154 | 0.3131 | 0.6978 | 0.3094 |
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+ | No log | 2.3284 | 156 | 0.3521 | 0.7069 | 0.3491 |
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+ | No log | 2.3582 | 158 | 0.3785 | 0.7286 | 0.3758 |
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+ | No log | 2.3881 | 160 | 0.3664 | 0.7315 | 0.3636 |
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+ | No log | 2.4179 | 162 | 0.3289 | 0.7003 | 0.3256 |
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+ | No log | 2.4478 | 164 | 0.3151 | 0.6734 | 0.3113 |
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+ | No log | 2.4776 | 166 | 0.3182 | 0.6390 | 0.3144 |
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+ | No log | 2.5075 | 168 | 0.3112 | 0.6862 | 0.3077 |
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+ | No log | 2.5373 | 170 | 0.3238 | 0.7096 | 0.3208 |
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+ | No log | 2.5672 | 172 | 0.3357 | 0.7111 | 0.3329 |
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+ | No log | 2.5970 | 174 | 0.3280 | 0.7128 | 0.3250 |
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+ | No log | 2.6269 | 176 | 0.3196 | 0.7017 | 0.3163 |
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+ | No log | 2.6567 | 178 | 0.3192 | 0.6981 | 0.3157 |
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+ | No log | 2.6866 | 180 | 0.3262 | 0.7028 | 0.3228 |
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+ | No log | 2.7164 | 182 | 0.3285 | 0.7151 | 0.3250 |
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+ | No log | 2.7463 | 184 | 0.3391 | 0.7314 | 0.3356 |
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+ | No log | 2.7761 | 186 | 0.3273 | 0.7103 | 0.3235 |
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+ | No log | 2.8060 | 188 | 0.3270 | 0.7039 | 0.3232 |
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+ | No log | 2.8358 | 190 | 0.3225 | 0.6956 | 0.3187 |
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+ | No log | 2.8657 | 192 | 0.3170 | 0.6903 | 0.3133 |
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+ | No log | 2.8955 | 194 | 0.3177 | 0.7129 | 0.3142 |
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+ | No log | 2.9254 | 196 | 0.3411 | 0.7205 | 0.3379 |
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+ | No log | 2.9552 | 198 | 0.3547 | 0.7257 | 0.3518 |
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+ | No log | 2.9851 | 200 | 0.3820 | 0.7394 | 0.3794 |
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+ | No log | 3.0149 | 202 | 0.3734 | 0.7259 | 0.3707 |
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+ | No log | 3.0448 | 204 | 0.3504 | 0.7125 | 0.3477 |
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+ | No log | 3.0746 | 206 | 0.3331 | 0.7062 | 0.3303 |
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+ | No log | 3.1045 | 208 | 0.3297 | 0.7034 | 0.3268 |
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+ | No log | 3.1343 | 210 | 0.3148 | 0.7056 | 0.3116 |
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+ | No log | 3.1642 | 212 | 0.3094 | 0.6964 | 0.3059 |
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+ | No log | 3.1940 | 214 | 0.3136 | 0.7063 | 0.3100 |
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+ | No log | 3.2239 | 216 | 0.3093 | 0.6969 | 0.3055 |
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+ | No log | 3.2537 | 218 | 0.3175 | 0.7023 | 0.3136 |
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+ | No log | 3.2836 | 220 | 0.3284 | 0.7090 | 0.3245 |
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+ | No log | 3.3134 | 222 | 0.3512 | 0.7502 | 0.3474 |
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+ | No log | 3.3433 | 224 | 0.3781 | 0.7593 | 0.3745 |
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+ | No log | 3.3731 | 226 | 0.3766 | 0.7631 | 0.3730 |
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+ | No log | 3.4030 | 228 | 0.3435 | 0.7400 | 0.3397 |
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+ | No log | 3.4328 | 230 | 0.3188 | 0.6970 | 0.3148 |
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+ | No log | 3.4627 | 232 | 0.3182 | 0.6951 | 0.3142 |
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+ | No log | 3.4925 | 234 | 0.3306 | 0.7232 | 0.3268 |
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+ | No log | 3.5224 | 236 | 0.3722 | 0.7445 | 0.3687 |
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+ | No log | 3.5522 | 238 | 0.4429 | 0.7601 | 0.4397 |
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+ | No log | 3.5821 | 240 | 0.4691 | 0.7670 | 0.4660 |
171
+ | No log | 3.6119 | 242 | 0.4352 | 0.7723 | 0.4317 |
172
+ | No log | 3.6418 | 244 | 0.3737 | 0.7367 | 0.3698 |
173
+ | No log | 3.6716 | 246 | 0.3465 | 0.7244 | 0.3422 |
174
+ | No log | 3.7015 | 248 | 0.3303 | 0.7140 | 0.3257 |
175
+ | No log | 3.7313 | 250 | 0.3240 | 0.7111 | 0.3192 |
176
+ | No log | 3.7612 | 252 | 0.3242 | 0.7154 | 0.3193 |
177
+ | No log | 3.7910 | 254 | 0.3226 | 0.7155 | 0.3176 |
178
+ | No log | 3.8209 | 256 | 0.3210 | 0.7185 | 0.3162 |
179
+ | No log | 3.8507 | 258 | 0.3214 | 0.7133 | 0.3167 |
180
+ | No log | 3.8806 | 260 | 0.3333 | 0.7208 | 0.3289 |
181
+ | No log | 3.9104 | 262 | 0.3389 | 0.7181 | 0.3347 |
182
+ | No log | 3.9403 | 264 | 0.3283 | 0.7208 | 0.3240 |
183
+ | No log | 3.9701 | 266 | 0.3182 | 0.7157 | 0.3137 |
184
+ | No log | 4.0 | 268 | 0.3059 | 0.7117 | 0.3012 |
185
+ | No log | 4.0299 | 270 | 0.3039 | 0.6871 | 0.2992 |
186
+ | No log | 4.0597 | 272 | 0.3037 | 0.6848 | 0.2990 |
187
+ | No log | 4.0896 | 274 | 0.3022 | 0.7070 | 0.2977 |
188
+ | No log | 4.1194 | 276 | 0.3065 | 0.7124 | 0.3022 |
189
+ | No log | 4.1493 | 278 | 0.3156 | 0.7123 | 0.3116 |
190
+ | No log | 4.1791 | 280 | 0.3377 | 0.7243 | 0.3341 |
191
+ | No log | 4.2090 | 282 | 0.3639 | 0.7213 | 0.3605 |
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+ | No log | 4.2388 | 284 | 0.3704 | 0.7328 | 0.3671 |
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+ | No log | 4.2687 | 286 | 0.3574 | 0.7297 | 0.3539 |
194
+ | No log | 4.2985 | 288 | 0.3356 | 0.7157 | 0.3318 |
195
+ | No log | 4.3284 | 290 | 0.3173 | 0.7171 | 0.3133 |
196
+ | No log | 4.3582 | 292 | 0.3088 | 0.7137 | 0.3046 |
197
+ | No log | 4.3881 | 294 | 0.3061 | 0.7066 | 0.3018 |
198
+ | No log | 4.4179 | 296 | 0.3072 | 0.7126 | 0.3029 |
199
+ | No log | 4.4478 | 298 | 0.3102 | 0.7178 | 0.3060 |
200
+ | No log | 4.4776 | 300 | 0.3153 | 0.7152 | 0.3111 |
201
+ | No log | 4.5075 | 302 | 0.3223 | 0.7218 | 0.3182 |
202
+ | No log | 4.5373 | 304 | 0.3316 | 0.7264 | 0.3276 |
203
+ | No log | 4.5672 | 306 | 0.3417 | 0.7355 | 0.3378 |
204
+ | No log | 4.5970 | 308 | 0.3499 | 0.7352 | 0.3462 |
205
+ | No log | 4.6269 | 310 | 0.3548 | 0.7438 | 0.3511 |
206
+ | No log | 4.6567 | 312 | 0.3536 | 0.7427 | 0.3499 |
207
+ | No log | 4.6866 | 314 | 0.3519 | 0.7407 | 0.3482 |
208
+ | No log | 4.7164 | 316 | 0.3472 | 0.7299 | 0.3434 |
209
+ | No log | 4.7463 | 318 | 0.3398 | 0.7326 | 0.3359 |
210
+ | No log | 4.7761 | 320 | 0.3326 | 0.7288 | 0.3286 |
211
+ | No log | 4.8060 | 322 | 0.3284 | 0.7268 | 0.3245 |
212
+ | No log | 4.8358 | 324 | 0.3274 | 0.7248 | 0.3234 |
213
+ | No log | 4.8657 | 326 | 0.3274 | 0.7248 | 0.3235 |
214
+ | No log | 4.8955 | 328 | 0.3284 | 0.7248 | 0.3244 |
215
+ | No log | 4.9254 | 330 | 0.3289 | 0.7268 | 0.3250 |
216
+ | No log | 4.9552 | 332 | 0.3288 | 0.7268 | 0.3248 |
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+ | No log | 4.9851 | 334 | 0.3287 | 0.7248 | 0.3247 |
218
 
219
 
220
  ### Framework versions
model.safetensors CHANGED
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  size 433267692
 
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