Commit
•
0a190fd
1
Parent(s):
62be33c
Training in progress, step 32000
Browse files- README.md +356 -0
- added_tokens.json +7 -0
- all_results.json +14 -0
- config.json +28 -0
- eval_results.json +9 -0
- merges.txt +0 -0
- pytorch_model.bin +3 -0
- special_tokens_map.json +16 -0
- tokenizer.json +0 -0
- tokenizer_config.json +68 -0
- train_results.json +8 -0
- trainer_state.json +3328 -0
- training_args.bin +3 -0
- vocab.json +0 -0
README.md
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| 1 |
+
---
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license: mit
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base_model: cardiffnlp/twitter-roberta-base-2019-90m
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tags:
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- generated_from_trainer
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model-index:
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- name: 2020-Q4-50p-filtered-random
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results: []
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---
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| 11 |
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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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+
# 2020-Q4-50p-filtered-random
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This model is a fine-tuned version of [cardiffnlp/twitter-roberta-base-2019-90m](https://huggingface.co/cardiffnlp/twitter-roberta-base-2019-90m) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.2570
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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: 4.1e-07
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- train_batch_size: 16
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- eval_batch_size: 16
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-08
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- lr_scheduler_type: linear
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- training_steps: 2400000
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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| 48 |
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|:-------------:|:-----:|:-------:|:---------------:|
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| 49 |
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| No log | 0.03 | 8000 | 2.5888 |
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| 50 |
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| 2.8176 | 0.07 | 16000 | 2.4814 |
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| 51 |
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| 2.8176 | 0.1 | 24000 | 2.4264 |
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| 52 |
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| 2.5609 | 0.13 | 32000 | 2.3993 |
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| 53 |
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| 2.5609 | 0.17 | 40000 | 2.3761 |
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| 54 |
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| 2.4969 | 0.2 | 48000 | 2.3624 |
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| 55 |
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| 2.4969 | 0.24 | 56000 | 2.3481 |
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| 2.48 | 0.27 | 64000 | 2.3399 |
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| 2.48 | 0.3 | 72000 | 2.3289 |
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| 58 |
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| 2.451 | 0.34 | 80000 | 2.3221 |
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| 59 |
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| 2.451 | 0.37 | 88000 | 2.3183 |
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| 60 |
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| 2.4367 | 0.4 | 96000 | 2.3221 |
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| 61 |
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| 2.4367 | 0.44 | 104000 | 2.3142 |
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| 62 |
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| 2.4388 | 0.47 | 112000 | 2.3028 |
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| 63 |
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| 2.4388 | 0.51 | 120000 | 2.3066 |
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| 64 |
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| 2.4215 | 0.54 | 128000 | 2.3013 |
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| 65 |
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| 2.4215 | 0.57 | 136000 | 2.3039 |
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| 66 |
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| 2.4178 | 0.61 | 144000 | 2.2907 |
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| 67 |
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| 2.4178 | 0.64 | 152000 | 2.2996 |
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| 68 |
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| 2.4103 | 0.67 | 160000 | 2.2943 |
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| 69 |
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| 2.4103 | 0.71 | 168000 | 2.2900 |
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| 70 |
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| 2.4122 | 0.74 | 176000 | 2.2902 |
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| 71 |
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| 2.4122 | 0.77 | 184000 | 2.2961 |
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| 72 |
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| 2.4173 | 0.81 | 192000 | 2.2906 |
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| 2.4173 | 0.84 | 200000 | 2.2925 |
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| 74 |
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| 2.4067 | 0.88 | 208000 | 2.2911 |
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| 75 |
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| 2.4067 | 0.91 | 216000 | 2.2844 |
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| 2.4059 | 0.94 | 224000 | 2.2855 |
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| 2.4059 | 0.98 | 232000 | 2.2811 |
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| 2.4089 | 1.01 | 240000 | 2.2788 |
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| 2.4089 | 1.04 | 248000 | 2.2796 |
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| 2.4034 | 1.08 | 256000 | 2.2827 |
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| 2.4034 | 1.11 | 264000 | 2.2803 |
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| 2.408 | 1.15 | 272000 | 2.2746 |
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| 2.408 | 1.18 | 280000 | 2.2851 |
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| 2.3985 | 1.21 | 288000 | 2.2781 |
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| 2.3985 | 1.25 | 296000 | 2.2795 |
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| 2.4009 | 1.28 | 304000 | 2.2777 |
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| 2.4009 | 1.31 | 312000 | 2.2770 |
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| 2.4017 | 1.35 | 320000 | 2.2763 |
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| 2.4017 | 1.38 | 328000 | 2.2734 |
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| 2.4056 | 1.41 | 336000 | 2.2758 |
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| 2.4056 | 1.45 | 344000 | 2.2763 |
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| 2.4017 | 1.48 | 352000 | 2.2700 |
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| 2.4017 | 1.52 | 360000 | 2.2736 |
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| 2.3993 | 1.55 | 368000 | 2.2763 |
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| 2.3993 | 1.58 | 376000 | 2.2792 |
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| 2.3994 | 1.62 | 384000 | 2.2666 |
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| 2.3994 | 1.65 | 392000 | 2.2699 |
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| 2.3969 | 1.68 | 400000 | 2.2753 |
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| 2.3969 | 1.72 | 408000 | 2.2707 |
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| 2.4094 | 1.75 | 416000 | 2.2731 |
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| 2.4094 | 1.79 | 424000 | 2.2709 |
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| 2.4102 | 1.82 | 432000 | 2.2623 |
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| 2.4102 | 1.85 | 440000 | 2.2751 |
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| 2.4042 | 1.89 | 448000 | 2.2728 |
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| 2.4042 | 1.92 | 456000 | 2.2714 |
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| 2.3991 | 1.95 | 464000 | 2.2634 |
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| 2.3991 | 1.99 | 472000 | 2.2695 |
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| 2.3976 | 2.02 | 480000 | 2.2731 |
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| 2.3976 | 2.05 | 488000 | 2.2736 |
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| 2.4019 | 2.09 | 496000 | 2.2803 |
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| 111 |
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| 2.4019 | 2.12 | 504000 | 2.2699 |
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| 112 |
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| 2.4044 | 2.16 | 512000 | 2.2731 |
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| 2.4044 | 2.19 | 520000 | 2.2709 |
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| 114 |
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| 2.3989 | 2.22 | 528000 | 2.2716 |
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| 115 |
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| 2.3989 | 2.26 | 536000 | 2.2668 |
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| 116 |
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| 2.4068 | 2.29 | 544000 | 2.2728 |
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| 117 |
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| 2.4068 | 2.32 | 552000 | 2.2709 |
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| 118 |
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| 2.4047 | 2.36 | 560000 | 2.2683 |
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| 119 |
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| 2.4047 | 2.39 | 568000 | 2.2731 |
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| 120 |
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| 2.3976 | 2.43 | 576000 | 2.2676 |
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| 2.3976 | 2.46 | 584000 | 2.2736 |
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| 122 |
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| 2.3994 | 2.49 | 592000 | 2.2624 |
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| 123 |
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| 2.3994 | 2.53 | 600000 | 2.2773 |
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| 124 |
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| 2.3997 | 2.56 | 608000 | 2.2719 |
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| 125 |
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| 2.3997 | 2.59 | 616000 | 2.2701 |
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| 126 |
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| 2.4042 | 2.63 | 624000 | 2.2695 |
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| 127 |
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| 2.4042 | 2.66 | 632000 | 2.2666 |
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| 128 |
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| 2.3994 | 2.69 | 640000 | 2.2719 |
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| 129 |
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| 2.3994 | 2.73 | 648000 | 2.2686 |
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| 2.3953 | 2.76 | 656000 | 2.2623 |
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| 131 |
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| 2.3953 | 2.8 | 664000 | 2.2662 |
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| 132 |
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| 2.402 | 2.83 | 672000 | 2.2707 |
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| 133 |
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| 2.402 | 2.86 | 680000 | 2.2662 |
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| 134 |
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| 2.3929 | 2.9 | 688000 | 2.2726 |
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| 135 |
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| 2.3929 | 2.93 | 696000 | 2.2682 |
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| 136 |
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| 2.3977 | 2.96 | 704000 | 2.2634 |
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| 137 |
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| 2.3977 | 3.0 | 712000 | 2.2685 |
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| 138 |
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| 2.4022 | 3.03 | 720000 | 2.2693 |
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| 139 |
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| 2.4022 | 3.07 | 728000 | 2.2666 |
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| 140 |
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| 2.4046 | 3.1 | 736000 | 2.2690 |
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| 141 |
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| 2.4046 | 3.13 | 744000 | 2.2641 |
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| 2.3977 | 3.17 | 752000 | 2.2658 |
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| 2.3977 | 3.2 | 760000 | 2.2645 |
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| 2.4015 | 3.23 | 768000 | 2.2619 |
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| 2.4015 | 3.27 | 776000 | 2.2671 |
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| 2.393 | 3.3 | 784000 | 2.2694 |
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| 2.393 | 3.33 | 792000 | 2.2662 |
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| 2.3907 | 3.37 | 800000 | 2.2691 |
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| 2.3907 | 3.4 | 808000 | 2.2679 |
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| 2.3987 | 3.44 | 816000 | 2.2688 |
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| 2.3987 | 3.47 | 824000 | 2.2655 |
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| 2.4116 | 3.5 | 832000 | 2.2668 |
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| 2.4116 | 3.54 | 840000 | 2.2675 |
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| 2.3913 | 3.57 | 848000 | 2.2689 |
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| 2.3913 | 3.6 | 856000 | 2.2642 |
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| 2.3974 | 3.64 | 864000 | 2.2667 |
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| 2.3974 | 3.67 | 872000 | 2.2717 |
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| 2.4046 | 3.71 | 880000 | 2.2661 |
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| 2.4046 | 3.74 | 888000 | 2.2705 |
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| 2.4006 | 3.77 | 896000 | 2.2637 |
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| 2.4006 | 3.81 | 904000 | 2.2635 |
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| 2.3987 | 3.84 | 912000 | 2.2642 |
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| 2.3987 | 3.87 | 920000 | 2.2691 |
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| 2.4068 | 3.91 | 928000 | 2.2689 |
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| 2.4068 | 3.94 | 936000 | 2.2730 |
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| 2.4092 | 3.97 | 944000 | 2.2644 |
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| 2.4092 | 4.01 | 952000 | 2.2706 |
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| 2.4035 | 4.04 | 960000 | 2.2671 |
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| 2.4035 | 4.08 | 968000 | 2.2562 |
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| 2.4005 | 4.11 | 976000 | 2.2622 |
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| 171 |
+
| 2.4005 | 4.14 | 984000 | 2.2642 |
|
| 172 |
+
| 2.406 | 4.18 | 992000 | 2.2625 |
|
| 173 |
+
| 2.406 | 4.21 | 1000000 | 2.2662 |
|
| 174 |
+
| 2.3972 | 4.24 | 1008000 | 2.2658 |
|
| 175 |
+
| 2.3972 | 4.28 | 1016000 | 2.2668 |
|
| 176 |
+
| 2.3937 | 4.31 | 1024000 | 2.2593 |
|
| 177 |
+
| 2.3937 | 4.35 | 1032000 | 2.2712 |
|
| 178 |
+
| 2.3982 | 4.38 | 1040000 | 2.2695 |
|
| 179 |
+
| 2.3982 | 4.41 | 1048000 | 2.2684 |
|
| 180 |
+
| 2.4034 | 4.45 | 1056000 | 2.2643 |
|
| 181 |
+
| 2.4034 | 4.48 | 1064000 | 2.2665 |
|
| 182 |
+
| 2.3996 | 4.51 | 1072000 | 2.2692 |
|
| 183 |
+
| 2.3996 | 4.55 | 1080000 | 2.2628 |
|
| 184 |
+
| 2.4054 | 4.58 | 1088000 | 2.2673 |
|
| 185 |
+
| 2.4054 | 4.61 | 1096000 | 2.2577 |
|
| 186 |
+
| 2.4039 | 4.65 | 1104000 | 2.2671 |
|
| 187 |
+
| 2.4039 | 4.68 | 1112000 | 2.2586 |
|
| 188 |
+
| 2.4033 | 4.72 | 1120000 | 2.2730 |
|
| 189 |
+
| 2.4033 | 4.75 | 1128000 | 2.2655 |
|
| 190 |
+
| 2.4036 | 4.78 | 1136000 | 2.2694 |
|
| 191 |
+
| 2.4036 | 4.82 | 1144000 | 2.2630 |
|
| 192 |
+
| 2.4036 | 4.85 | 1152000 | 2.2618 |
|
| 193 |
+
| 2.4036 | 4.88 | 1160000 | 2.2665 |
|
| 194 |
+
| 2.4005 | 4.92 | 1168000 | 2.2609 |
|
| 195 |
+
| 2.4005 | 4.95 | 1176000 | 2.2617 |
|
| 196 |
+
| 2.4065 | 4.99 | 1184000 | 2.2646 |
|
| 197 |
+
| 2.4065 | 5.02 | 1192000 | 2.2606 |
|
| 198 |
+
| 2.4044 | 5.05 | 1200000 | 2.2656 |
|
| 199 |
+
| 2.4044 | 5.09 | 1208000 | 2.2630 |
|
| 200 |
+
| 2.3997 | 5.12 | 1216000 | 2.2737 |
|
| 201 |
+
| 2.3997 | 5.15 | 1224000 | 2.2762 |
|
| 202 |
+
| 2.407 | 5.19 | 1232000 | 2.2669 |
|
| 203 |
+
| 2.407 | 5.22 | 1240000 | 2.2695 |
|
| 204 |
+
| 2.4013 | 5.25 | 1248000 | 2.2704 |
|
| 205 |
+
| 2.4013 | 5.29 | 1256000 | 2.2612 |
|
| 206 |
+
| 2.4118 | 5.32 | 1264000 | 2.2654 |
|
| 207 |
+
| 2.4118 | 5.36 | 1272000 | 2.2683 |
|
| 208 |
+
| 2.3953 | 5.39 | 1280000 | 2.2628 |
|
| 209 |
+
| 2.3953 | 5.42 | 1288000 | 2.2605 |
|
| 210 |
+
| 2.3973 | 5.46 | 1296000 | 2.2667 |
|
| 211 |
+
| 2.3973 | 5.49 | 1304000 | 2.2640 |
|
| 212 |
+
| 2.4027 | 5.52 | 1312000 | 2.2619 |
|
| 213 |
+
| 2.4027 | 5.56 | 1320000 | 2.2687 |
|
| 214 |
+
| 2.3967 | 5.59 | 1328000 | 2.2598 |
|
| 215 |
+
| 2.3967 | 5.63 | 1336000 | 2.2621 |
|
| 216 |
+
| 2.4028 | 5.66 | 1344000 | 2.2602 |
|
| 217 |
+
| 2.4028 | 5.69 | 1352000 | 2.2713 |
|
| 218 |
+
| 2.4053 | 5.73 | 1360000 | 2.2623 |
|
| 219 |
+
| 2.4053 | 5.76 | 1368000 | 2.2697 |
|
| 220 |
+
| 2.3987 | 5.79 | 1376000 | 2.2638 |
|
| 221 |
+
| 2.3987 | 5.83 | 1384000 | 2.2601 |
|
| 222 |
+
| 2.3987 | 5.86 | 1392000 | 2.2642 |
|
| 223 |
+
| 2.3987 | 5.89 | 1400000 | 2.2656 |
|
| 224 |
+
| 2.401 | 5.93 | 1408000 | 2.2712 |
|
| 225 |
+
| 2.401 | 5.96 | 1416000 | 2.2639 |
|
| 226 |
+
| 2.4011 | 6.0 | 1424000 | 2.2646 |
|
| 227 |
+
| 2.4011 | 6.03 | 1432000 | 2.2669 |
|
| 228 |
+
| 2.4022 | 6.06 | 1440000 | 2.2619 |
|
| 229 |
+
| 2.4022 | 6.1 | 1448000 | 2.2580 |
|
| 230 |
+
| 2.3998 | 6.13 | 1456000 | 2.2612 |
|
| 231 |
+
| 2.3998 | 6.16 | 1464000 | 2.2652 |
|
| 232 |
+
| 2.3999 | 6.2 | 1472000 | 2.2610 |
|
| 233 |
+
| 2.3999 | 6.23 | 1480000 | 2.2567 |
|
| 234 |
+
| 2.3984 | 6.27 | 1488000 | 2.2590 |
|
| 235 |
+
| 2.3984 | 6.3 | 1496000 | 2.2565 |
|
| 236 |
+
| 2.4017 | 6.33 | 1504000 | 2.2658 |
|
| 237 |
+
| 2.4017 | 6.37 | 1512000 | 2.2626 |
|
| 238 |
+
| 2.4055 | 6.4 | 1520000 | 2.2656 |
|
| 239 |
+
| 2.4055 | 6.43 | 1528000 | 2.2622 |
|
| 240 |
+
| 2.3959 | 6.47 | 1536000 | 2.2691 |
|
| 241 |
+
| 2.3959 | 6.5 | 1544000 | 2.2604 |
|
| 242 |
+
| 2.4016 | 6.53 | 1552000 | 2.2599 |
|
| 243 |
+
| 2.4016 | 6.57 | 1560000 | 2.2655 |
|
| 244 |
+
| 2.3986 | 6.6 | 1568000 | 2.2684 |
|
| 245 |
+
| 2.3986 | 6.64 | 1576000 | 2.2716 |
|
| 246 |
+
| 2.4051 | 6.67 | 1584000 | 2.2605 |
|
| 247 |
+
| 2.4051 | 6.7 | 1592000 | 2.2569 |
|
| 248 |
+
| 2.4057 | 6.74 | 1600000 | 2.2687 |
|
| 249 |
+
| 2.4057 | 6.77 | 1608000 | 2.2571 |
|
| 250 |
+
| 2.3956 | 6.8 | 1616000 | 2.2664 |
|
| 251 |
+
| 2.3956 | 6.84 | 1624000 | 2.2612 |
|
| 252 |
+
| 2.4048 | 6.87 | 1632000 | 2.2643 |
|
| 253 |
+
| 2.4048 | 6.91 | 1640000 | 2.2633 |
|
| 254 |
+
| 2.4042 | 6.94 | 1648000 | 2.2634 |
|
| 255 |
+
| 2.4042 | 6.97 | 1656000 | 2.2637 |
|
| 256 |
+
| 2.4008 | 7.01 | 1664000 | 2.2619 |
|
| 257 |
+
| 2.4008 | 7.04 | 1672000 | 2.2579 |
|
| 258 |
+
| 2.397 | 7.07 | 1680000 | 2.2628 |
|
| 259 |
+
| 2.397 | 7.11 | 1688000 | 2.2593 |
|
| 260 |
+
| 2.4044 | 7.14 | 1696000 | 2.2593 |
|
| 261 |
+
| 2.4044 | 7.17 | 1704000 | 2.2613 |
|
| 262 |
+
| 2.3979 | 7.21 | 1712000 | 2.2685 |
|
| 263 |
+
| 2.3979 | 7.24 | 1720000 | 2.2683 |
|
| 264 |
+
| 2.4017 | 7.28 | 1728000 | 2.2611 |
|
| 265 |
+
| 2.4017 | 7.31 | 1736000 | 2.2672 |
|
| 266 |
+
| 2.4017 | 7.34 | 1744000 | 2.2577 |
|
| 267 |
+
| 2.4017 | 7.38 | 1752000 | 2.2609 |
|
| 268 |
+
| 2.4018 | 7.41 | 1760000 | 2.2567 |
|
| 269 |
+
| 2.4018 | 7.44 | 1768000 | 2.2661 |
|
| 270 |
+
| 2.3905 | 7.48 | 1776000 | 2.2671 |
|
| 271 |
+
| 2.3905 | 7.51 | 1784000 | 2.2663 |
|
| 272 |
+
| 2.4063 | 7.55 | 1792000 | 2.2619 |
|
| 273 |
+
| 2.4063 | 7.58 | 1800000 | 2.2587 |
|
| 274 |
+
| 2.4015 | 7.61 | 1808000 | 2.2584 |
|
| 275 |
+
| 2.4015 | 7.65 | 1816000 | 2.2580 |
|
| 276 |
+
| 2.3984 | 7.68 | 1824000 | 2.2586 |
|
| 277 |
+
| 2.3984 | 7.71 | 1832000 | 2.2620 |
|
| 278 |
+
| 2.3962 | 7.75 | 1840000 | 2.2584 |
|
| 279 |
+
| 2.3962 | 7.78 | 1848000 | 2.2607 |
|
| 280 |
+
| 2.3998 | 7.81 | 1856000 | 2.2638 |
|
| 281 |
+
| 2.3998 | 7.85 | 1864000 | 2.2629 |
|
| 282 |
+
| 2.4005 | 7.88 | 1872000 | 2.2716 |
|
| 283 |
+
| 2.4005 | 7.92 | 1880000 | 2.2623 |
|
| 284 |
+
| 2.4006 | 7.95 | 1888000 | 2.2555 |
|
| 285 |
+
| 2.4006 | 7.98 | 1896000 | 2.2653 |
|
| 286 |
+
| 2.3946 | 8.02 | 1904000 | 2.2629 |
|
| 287 |
+
| 2.3946 | 8.05 | 1912000 | 2.2654 |
|
| 288 |
+
| 2.3983 | 8.08 | 1920000 | 2.2623 |
|
| 289 |
+
| 2.3983 | 8.12 | 1928000 | 2.2544 |
|
| 290 |
+
| 2.4038 | 8.15 | 1936000 | 2.2605 |
|
| 291 |
+
| 2.4038 | 8.19 | 1944000 | 2.2622 |
|
| 292 |
+
| 2.399 | 8.22 | 1952000 | 2.2600 |
|
| 293 |
+
| 2.399 | 8.25 | 1960000 | 2.2629 |
|
| 294 |
+
| 2.3983 | 8.29 | 1968000 | 2.2621 |
|
| 295 |
+
| 2.3983 | 8.32 | 1976000 | 2.2609 |
|
| 296 |
+
| 2.4059 | 8.35 | 1984000 | 2.2705 |
|
| 297 |
+
| 2.4059 | 8.39 | 1992000 | 2.2572 |
|
| 298 |
+
| 2.4058 | 8.42 | 2000000 | 2.2602 |
|
| 299 |
+
| 2.4058 | 8.45 | 2008000 | 2.2626 |
|
| 300 |
+
| 2.3954 | 8.49 | 2016000 | 2.2668 |
|
| 301 |
+
| 2.3954 | 8.52 | 2024000 | 2.2599 |
|
| 302 |
+
| 2.3932 | 8.56 | 2032000 | 2.2643 |
|
| 303 |
+
| 2.3932 | 8.59 | 2040000 | 2.2559 |
|
| 304 |
+
| 2.4001 | 8.62 | 2048000 | 2.2614 |
|
| 305 |
+
| 2.4001 | 8.66 | 2056000 | 2.2577 |
|
| 306 |
+
| 2.3912 | 8.69 | 2064000 | 2.2665 |
|
| 307 |
+
| 2.3912 | 8.72 | 2072000 | 2.2576 |
|
| 308 |
+
| 2.4015 | 8.76 | 2080000 | 2.2672 |
|
| 309 |
+
| 2.4015 | 8.79 | 2088000 | 2.2598 |
|
| 310 |
+
| 2.4015 | 8.83 | 2096000 | 2.2599 |
|
| 311 |
+
| 2.4015 | 8.86 | 2104000 | 2.2641 |
|
| 312 |
+
| 2.399 | 8.89 | 2112000 | 2.2612 |
|
| 313 |
+
| 2.399 | 8.93 | 2120000 | 2.2607 |
|
| 314 |
+
| 2.3963 | 8.96 | 2128000 | 2.2633 |
|
| 315 |
+
| 2.3963 | 8.99 | 2136000 | 2.2567 |
|
| 316 |
+
| 2.3957 | 9.03 | 2144000 | 2.2630 |
|
| 317 |
+
| 2.3957 | 9.06 | 2152000 | 2.2597 |
|
| 318 |
+
| 2.3943 | 9.09 | 2160000 | 2.2624 |
|
| 319 |
+
| 2.3943 | 9.13 | 2168000 | 2.2599 |
|
| 320 |
+
| 2.4025 | 9.16 | 2176000 | 2.2578 |
|
| 321 |
+
| 2.4025 | 9.2 | 2184000 | 2.2640 |
|
| 322 |
+
| 2.3944 | 9.23 | 2192000 | 2.2562 |
|
| 323 |
+
| 2.3944 | 9.26 | 2200000 | 2.2660 |
|
| 324 |
+
| 2.3964 | 9.3 | 2208000 | 2.2556 |
|
| 325 |
+
| 2.3964 | 9.33 | 2216000 | 2.2697 |
|
| 326 |
+
| 2.4026 | 9.36 | 2224000 | 2.2652 |
|
| 327 |
+
| 2.4026 | 9.4 | 2232000 | 2.2571 |
|
| 328 |
+
| 2.398 | 9.43 | 2240000 | 2.2555 |
|
| 329 |
+
| 2.398 | 9.47 | 2248000 | 2.2607 |
|
| 330 |
+
| 2.4038 | 9.5 | 2256000 | 2.2558 |
|
| 331 |
+
| 2.4038 | 9.53 | 2264000 | 2.2660 |
|
| 332 |
+
| 2.4027 | 9.57 | 2272000 | 2.2587 |
|
| 333 |
+
| 2.4027 | 9.6 | 2280000 | 2.2605 |
|
| 334 |
+
| 2.4025 | 9.63 | 2288000 | 2.2578 |
|
| 335 |
+
| 2.4025 | 9.67 | 2296000 | 2.2609 |
|
| 336 |
+
| 2.3969 | 9.7 | 2304000 | 2.2597 |
|
| 337 |
+
| 2.3969 | 9.73 | 2312000 | 2.2619 |
|
| 338 |
+
| 2.3886 | 9.77 | 2320000 | 2.2645 |
|
| 339 |
+
| 2.3886 | 9.8 | 2328000 | 2.2717 |
|
| 340 |
+
| 2.3942 | 9.84 | 2336000 | 2.2627 |
|
| 341 |
+
| 2.3942 | 9.87 | 2344000 | 2.2582 |
|
| 342 |
+
| 2.396 | 9.9 | 2352000 | 2.2634 |
|
| 343 |
+
| 2.396 | 9.94 | 2360000 | 2.2582 |
|
| 344 |
+
| 2.3998 | 9.97 | 2368000 | 2.2643 |
|
| 345 |
+
| 2.3998 | 10.0 | 2376000 | 2.2690 |
|
| 346 |
+
| 2.4014 | 10.04 | 2384000 | 2.2655 |
|
| 347 |
+
| 2.4014 | 10.07 | 2392000 | 2.2660 |
|
| 348 |
+
| 2.4004 | 10.11 | 2400000 | 2.2650 |
|
| 349 |
+
|
| 350 |
+
|
| 351 |
+
### Framework versions
|
| 352 |
+
|
| 353 |
+
- Transformers 4.35.0.dev0
|
| 354 |
+
- Pytorch 2.0.1+cu117
|
| 355 |
+
- Datasets 2.14.5
|
| 356 |
+
- Tokenizers 0.14.0
|
added_tokens.json
ADDED
|
@@ -0,0 +1,7 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"</s>": 2,
|
| 3 |
+
"<mask>": 50264,
|
| 4 |
+
"<pad>": 1,
|
| 5 |
+
"<s>": 0,
|
| 6 |
+
"<unk>": 3
|
| 7 |
+
}
|
all_results.json
ADDED
|
@@ -0,0 +1,14 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"epoch": 10.11,
|
| 3 |
+
"eval_loss": 2.256998062133789,
|
| 4 |
+
"eval_runtime": 219.4552,
|
| 5 |
+
"eval_samples": 200000,
|
| 6 |
+
"eval_samples_per_second": 911.348,
|
| 7 |
+
"eval_steps_per_second": 56.959,
|
| 8 |
+
"perplexity": 9.554364464975754,
|
| 9 |
+
"train_loss": 2.4070425341796877,
|
| 10 |
+
"train_runtime": 215269.6307,
|
| 11 |
+
"train_samples": 3800001,
|
| 12 |
+
"train_samples_per_second": 178.381,
|
| 13 |
+
"train_steps_per_second": 11.149
|
| 14 |
+
}
|
config.json
ADDED
|
@@ -0,0 +1,28 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"_name_or_path": "DouglasPontes/2020-Q3-50p-filtered",
|
| 3 |
+
"architectures": [
|
| 4 |
+
"RobertaForMaskedLM"
|
| 5 |
+
],
|
| 6 |
+
"attention_probs_dropout_prob": 0.1,
|
| 7 |
+
"bos_token_id": 0,
|
| 8 |
+
"classifier_dropout": null,
|
| 9 |
+
"eos_token_id": 2,
|
| 10 |
+
"gradient_checkpointing": false,
|
| 11 |
+
"hidden_act": "gelu",
|
| 12 |
+
"hidden_dropout_prob": 0.1,
|
| 13 |
+
"hidden_size": 768,
|
| 14 |
+
"initializer_range": 0.02,
|
| 15 |
+
"intermediate_size": 3072,
|
| 16 |
+
"layer_norm_eps": 1e-05,
|
| 17 |
+
"max_position_embeddings": 514,
|
| 18 |
+
"model_type": "roberta",
|
| 19 |
+
"num_attention_heads": 12,
|
| 20 |
+
"num_hidden_layers": 12,
|
| 21 |
+
"pad_token_id": 1,
|
| 22 |
+
"position_embedding_type": "absolute",
|
| 23 |
+
"torch_dtype": "float32",
|
| 24 |
+
"transformers_version": "4.35.0.dev0",
|
| 25 |
+
"type_vocab_size": 1,
|
| 26 |
+
"use_cache": true,
|
| 27 |
+
"vocab_size": 50265
|
| 28 |
+
}
|
eval_results.json
ADDED
|
@@ -0,0 +1,9 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"epoch": 10.11,
|
| 3 |
+
"eval_loss": 2.256998062133789,
|
| 4 |
+
"eval_runtime": 219.4552,
|
| 5 |
+
"eval_samples": 200000,
|
| 6 |
+
"eval_samples_per_second": 911.348,
|
| 7 |
+
"eval_steps_per_second": 56.959,
|
| 8 |
+
"perplexity": 9.554364464975754
|
| 9 |
+
}
|
merges.txt
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
pytorch_model.bin
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:3ffbba3feef269f1544463dce99a88caf6e9790623d34267efa3e9e3d3fe20a1
|
| 3 |
+
size 498859189
|
special_tokens_map.json
ADDED
|
@@ -0,0 +1,16 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"additional_special_tokens": [
|
| 3 |
+
"<s>",
|
| 4 |
+
"<pad>",
|
| 5 |
+
"</s>",
|
| 6 |
+
"<unk>",
|
| 7 |
+
"<mask>"
|
| 8 |
+
],
|
| 9 |
+
"bos_token": "<s>",
|
| 10 |
+
"cls_token": "<s>",
|
| 11 |
+
"eos_token": "</s>",
|
| 12 |
+
"mask_token": "<mask>",
|
| 13 |
+
"pad_token": "<pad>",
|
| 14 |
+
"sep_token": "</s>",
|
| 15 |
+
"unk_token": "<unk>"
|
| 16 |
+
}
|
tokenizer.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
tokenizer_config.json
ADDED
|
@@ -0,0 +1,68 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
|
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|
|
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|
|
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|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
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|
|
|
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|
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|
|
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|
|
|
|
|
|
|
|
|
|
|
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|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"add_prefix_space": false,
|
| 3 |
+
"added_tokens_decoder": {
|
| 4 |
+
"0": {
|
| 5 |
+
"content": "<s>",
|
| 6 |
+
"lstrip": false,
|
| 7 |
+
"normalized": false,
|
| 8 |
+
"rstrip": false,
|
| 9 |
+
"single_word": false,
|
| 10 |
+
"special": true
|
| 11 |
+
},
|
| 12 |
+
"1": {
|
| 13 |
+
"content": "<pad>",
|
| 14 |
+
"lstrip": false,
|
| 15 |
+
"normalized": false,
|
| 16 |
+
"rstrip": false,
|
| 17 |
+
"single_word": false,
|
| 18 |
+
"special": true
|
| 19 |
+
},
|
| 20 |
+
"2": {
|
| 21 |
+
"content": "</s>",
|
| 22 |
+
"lstrip": false,
|
| 23 |
+
"normalized": false,
|
| 24 |
+
"rstrip": false,
|
| 25 |
+
"single_word": false,
|
| 26 |
+
"special": true
|
| 27 |
+
},
|
| 28 |
+
"3": {
|
| 29 |
+
"content": "<unk>",
|
| 30 |
+
"lstrip": false,
|
| 31 |
+
"normalized": false,
|
| 32 |
+
"rstrip": false,
|
| 33 |
+
"single_word": false,
|
| 34 |
+
"special": true
|
| 35 |
+
},
|
| 36 |
+
"50264": {
|
| 37 |
+
"content": "<mask>",
|
| 38 |
+
"lstrip": true,
|
| 39 |
+
"normalized": false,
|
| 40 |
+
"rstrip": false,
|
| 41 |
+
"single_word": false,
|
| 42 |
+
"special": true
|
| 43 |
+
}
|
| 44 |
+
},
|
| 45 |
+
"additional_special_tokens": [
|
| 46 |
+
"<s>",
|
| 47 |
+
"<pad>",
|
| 48 |
+
"</s>",
|
| 49 |
+
"<unk>",
|
| 50 |
+
"<mask>"
|
| 51 |
+
],
|
| 52 |
+
"bos_token": "<s>",
|
| 53 |
+
"clean_up_tokenization_spaces": true,
|
| 54 |
+
"cls_token": "<s>",
|
| 55 |
+
"eos_token": "</s>",
|
| 56 |
+
"errors": "replace",
|
| 57 |
+
"mask_token": "<mask>",
|
| 58 |
+
"max_length": 512,
|
| 59 |
+
"model_max_length": 512,
|
| 60 |
+
"pad_token": "<pad>",
|
| 61 |
+
"sep_token": "</s>",
|
| 62 |
+
"stride": 0,
|
| 63 |
+
"tokenizer_class": "RobertaTokenizer",
|
| 64 |
+
"trim_offsets": true,
|
| 65 |
+
"truncation_side": "right",
|
| 66 |
+
"truncation_strategy": "longest_first",
|
| 67 |
+
"unk_token": "<unk>"
|
| 68 |
+
}
|
train_results.json
ADDED
|
@@ -0,0 +1,8 @@
|
|
|
|
|
|
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|
|
|
|
|
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|
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|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"epoch": 10.11,
|
| 3 |
+
"train_loss": 2.4070425341796877,
|
| 4 |
+
"train_runtime": 215269.6307,
|
| 5 |
+
"train_samples": 3800001,
|
| 6 |
+
"train_samples_per_second": 178.381,
|
| 7 |
+
"train_steps_per_second": 11.149
|
| 8 |
+
}
|
trainer_state.json
ADDED
|
@@ -0,0 +1,3328 @@
|
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|
| 1 |
+
{
|
| 2 |
+
"best_metric": 2.2555091381073,
|
| 3 |
+
"best_model_checkpoint": "./model_tweets_2020_Q4_50/checkpoint-1888000",
|
| 4 |
+
"epoch": 10.105220609597433,
|
| 5 |
+
"eval_steps": 8000,
|
| 6 |
+
"global_step": 2400000,
|
| 7 |
+
"is_hyper_param_search": false,
|
| 8 |
+
"is_local_process_zero": true,
|
| 9 |
+
"is_world_process_zero": true,
|
| 10 |
+
"log_history": [
|
| 11 |
+
{
|
| 12 |
+
"epoch": 0.03,
|
| 13 |
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vocab.json
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