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 +9 -0
- tokenizer.json +0 -0
- tokenizer_config.json +62 -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-Q3-75p-filtered
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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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# 2020-Q3-75p-filtered
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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: 3.1267
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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 | 0.07 | 8000 | 3.4513 |
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| 50 |
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| 3.6645 | 0.14 | 16000 | 3.3790 |
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| 51 |
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| 3.6645 | 0.2 | 24000 | 3.3226 |
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| 52 |
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| 3.4678 | 0.27 | 32000 | 3.2901 |
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| 53 |
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| 3.4678 | 0.34 | 40000 | 3.2590 |
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| 54 |
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| 3.4118 | 0.41 | 48000 | 3.2534 |
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| 55 |
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| 3.4118 | 0.47 | 56000 | 3.2357 |
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| 56 |
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| 3.3843 | 0.54 | 64000 | 3.2228 |
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| 57 |
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| 3.3843 | 0.61 | 72000 | 3.2331 |
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| 58 |
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| 3.3633 | 0.68 | 80000 | 3.2047 |
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| 59 |
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| 3.3633 | 0.74 | 88000 | 3.2138 |
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| 60 |
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| 3.3474 | 0.81 | 96000 | 3.2050 |
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| 61 |
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| 3.3474 | 0.88 | 104000 | 3.2051 |
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| 62 |
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| 3.3414 | 0.95 | 112000 | 3.1930 |
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| 63 |
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| 3.3414 | 1.01 | 120000 | 3.2002 |
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| 64 |
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| 3.335 | 1.08 | 128000 | 3.1920 |
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| 65 |
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| 3.335 | 1.15 | 136000 | 3.1914 |
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| 66 |
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| 3.3283 | 1.22 | 144000 | 3.1853 |
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| 67 |
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| 3.3283 | 1.28 | 152000 | 3.1825 |
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| 68 |
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| 3.3276 | 1.35 | 160000 | 3.1827 |
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| 69 |
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| 3.3276 | 1.42 | 168000 | 3.1756 |
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| 70 |
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| 3.323 | 1.49 | 176000 | 3.1865 |
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| 71 |
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| 3.323 | 1.56 | 184000 | 3.1749 |
|
| 72 |
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| 3.3275 | 1.62 | 192000 | 3.1782 |
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| 73 |
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| 3.3275 | 1.69 | 200000 | 3.1676 |
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| 74 |
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| 3.3309 | 1.76 | 208000 | 3.1832 |
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| 75 |
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| 3.3309 | 1.83 | 216000 | 3.1744 |
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| 76 |
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| 3.3166 | 1.89 | 224000 | 3.1645 |
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| 77 |
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| 3.3166 | 1.96 | 232000 | 3.1770 |
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| 78 |
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| 3.3206 | 2.03 | 240000 | 3.1656 |
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| 79 |
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| 3.3206 | 2.1 | 248000 | 3.1561 |
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| 80 |
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| 3.3228 | 2.16 | 256000 | 3.1665 |
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| 81 |
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| 3.3228 | 2.23 | 264000 | 3.1657 |
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| 82 |
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| 3.3208 | 2.3 | 272000 | 3.1693 |
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| 83 |
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| 3.3208 | 2.37 | 280000 | 3.1778 |
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| 84 |
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| 3.3106 | 2.43 | 288000 | 3.1760 |
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| 85 |
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| 3.3106 | 2.5 | 296000 | 3.1664 |
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| 86 |
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| 3.3189 | 2.57 | 304000 | 3.1677 |
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| 87 |
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| 3.3189 | 2.64 | 312000 | 3.1600 |
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| 88 |
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| 3.319 | 2.7 | 320000 | 3.1570 |
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| 89 |
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| 3.319 | 2.77 | 328000 | 3.1699 |
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| 90 |
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| 3.3236 | 2.84 | 336000 | 3.1578 |
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| 91 |
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| 3.3236 | 2.91 | 344000 | 3.1665 |
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| 92 |
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| 3.3205 | 2.98 | 352000 | 3.1558 |
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| 93 |
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| 3.3205 | 3.04 | 360000 | 3.1678 |
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| 94 |
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| 3.3114 | 3.11 | 368000 | 3.1597 |
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| 95 |
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| 3.3114 | 3.18 | 376000 | 3.1618 |
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| 96 |
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| 3.3067 | 3.25 | 384000 | 3.1584 |
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| 97 |
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| 3.3067 | 3.31 | 392000 | 3.1597 |
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| 98 |
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| 3.314 | 3.38 | 400000 | 3.1565 |
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| 99 |
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| 3.314 | 3.45 | 408000 | 3.1612 |
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| 100 |
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| 3.3183 | 3.52 | 416000 | 3.1637 |
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| 101 |
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| 3.3183 | 3.58 | 424000 | 3.1569 |
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| 102 |
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| 3.318 | 3.65 | 432000 | 3.1576 |
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| 103 |
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| 3.318 | 3.72 | 440000 | 3.1639 |
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| 104 |
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| 3.3114 | 3.79 | 448000 | 3.1460 |
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| 105 |
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| 3.3114 | 3.85 | 456000 | 3.1611 |
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| 106 |
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| 3.3068 | 3.92 | 464000 | 3.1587 |
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| 107 |
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| 3.3068 | 3.99 | 472000 | 3.1542 |
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| 108 |
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| 3.3166 | 4.06 | 480000 | 3.1422 |
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| 109 |
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| 3.3166 | 4.12 | 488000 | 3.1604 |
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| 110 |
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| 3.3057 | 4.19 | 496000 | 3.1587 |
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| 111 |
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| 3.3057 | 4.26 | 504000 | 3.1576 |
|
| 112 |
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| 3.3176 | 4.33 | 512000 | 3.1602 |
|
| 113 |
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| 3.3176 | 4.4 | 520000 | 3.1544 |
|
| 114 |
+
| 3.3126 | 4.46 | 528000 | 3.1478 |
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| 115 |
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| 3.3126 | 4.53 | 536000 | 3.1520 |
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| 116 |
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| 3.3044 | 4.6 | 544000 | 3.1581 |
|
| 117 |
+
| 3.3044 | 4.67 | 552000 | 3.1625 |
|
| 118 |
+
| 3.3118 | 4.73 | 560000 | 3.1510 |
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| 119 |
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| 3.3118 | 4.8 | 568000 | 3.1548 |
|
| 120 |
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| 3.3085 | 4.87 | 576000 | 3.1539 |
|
| 121 |
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| 3.3085 | 4.94 | 584000 | 3.1503 |
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| 122 |
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| 3.3014 | 5.0 | 592000 | 3.1504 |
|
| 123 |
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| 3.3014 | 5.07 | 600000 | 3.1534 |
|
| 124 |
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| 3.3115 | 5.14 | 608000 | 3.1551 |
|
| 125 |
+
| 3.3115 | 5.21 | 616000 | 3.1493 |
|
| 126 |
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| 3.3079 | 5.27 | 624000 | 3.1427 |
|
| 127 |
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| 3.3079 | 5.34 | 632000 | 3.1500 |
|
| 128 |
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| 3.3138 | 5.41 | 640000 | 3.1546 |
|
| 129 |
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| 3.3138 | 5.48 | 648000 | 3.1482 |
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| 130 |
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| 3.3096 | 5.54 | 656000 | 3.1346 |
|
| 131 |
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| 3.3096 | 5.61 | 664000 | 3.1328 |
|
| 132 |
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| 3.3121 | 5.68 | 672000 | 3.1500 |
|
| 133 |
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| 3.3121 | 5.75 | 680000 | 3.1312 |
|
| 134 |
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| 3.3195 | 5.82 | 688000 | 3.1440 |
|
| 135 |
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| 3.3195 | 5.88 | 696000 | 3.1191 |
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| 136 |
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| 3.3091 | 5.95 | 704000 | 3.1397 |
|
| 137 |
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| 3.3091 | 6.02 | 712000 | 3.1485 |
|
| 138 |
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| 3.3089 | 6.09 | 720000 | 3.1340 |
|
| 139 |
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| 3.3089 | 6.15 | 728000 | 3.1385 |
|
| 140 |
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| 3.3062 | 6.22 | 736000 | 3.1358 |
|
| 141 |
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| 3.3062 | 6.29 | 744000 | 3.1296 |
|
| 142 |
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| 3.3102 | 6.36 | 752000 | 3.1260 |
|
| 143 |
+
| 3.3102 | 6.42 | 760000 | 3.1428 |
|
| 144 |
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| 3.3088 | 6.49 | 768000 | 3.1372 |
|
| 145 |
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| 3.3088 | 6.56 | 776000 | 3.1404 |
|
| 146 |
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| 3.3096 | 6.63 | 784000 | 3.1362 |
|
| 147 |
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| 3.3096 | 6.69 | 792000 | 3.1408 |
|
| 148 |
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| 3.3079 | 6.76 | 800000 | 3.1350 |
|
| 149 |
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| 3.3079 | 6.83 | 808000 | 3.1461 |
|
| 150 |
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| 3.3099 | 6.9 | 816000 | 3.1420 |
|
| 151 |
+
| 3.3099 | 6.96 | 824000 | 3.1213 |
|
| 152 |
+
| 3.3015 | 7.03 | 832000 | 3.1366 |
|
| 153 |
+
| 3.3015 | 7.1 | 840000 | 3.1401 |
|
| 154 |
+
| 3.3045 | 7.17 | 848000 | 3.1295 |
|
| 155 |
+
| 3.3045 | 7.24 | 856000 | 3.1323 |
|
| 156 |
+
| 3.3085 | 7.3 | 864000 | 3.1368 |
|
| 157 |
+
| 3.3085 | 7.37 | 872000 | 3.1275 |
|
| 158 |
+
| 3.3061 | 7.44 | 880000 | 3.1326 |
|
| 159 |
+
| 3.3061 | 7.51 | 888000 | 3.1377 |
|
| 160 |
+
| 3.309 | 7.57 | 896000 | 3.1407 |
|
| 161 |
+
| 3.309 | 7.64 | 904000 | 3.1324 |
|
| 162 |
+
| 3.3024 | 7.71 | 912000 | 3.1187 |
|
| 163 |
+
| 3.3024 | 7.78 | 920000 | 3.1514 |
|
| 164 |
+
| 3.2955 | 7.84 | 928000 | 3.1351 |
|
| 165 |
+
| 3.2955 | 7.91 | 936000 | 3.1308 |
|
| 166 |
+
| 3.3122 | 7.98 | 944000 | 3.1405 |
|
| 167 |
+
| 3.3122 | 8.05 | 952000 | 3.1291 |
|
| 168 |
+
| 3.304 | 8.11 | 960000 | 3.1244 |
|
| 169 |
+
| 3.304 | 8.18 | 968000 | 3.1409 |
|
| 170 |
+
| 3.3046 | 8.25 | 976000 | 3.1355 |
|
| 171 |
+
| 3.3046 | 8.32 | 984000 | 3.1416 |
|
| 172 |
+
| 3.3022 | 8.38 | 992000 | 3.1258 |
|
| 173 |
+
| 3.3022 | 8.45 | 1000000 | 3.1332 |
|
| 174 |
+
| 3.3004 | 8.52 | 1008000 | 3.1430 |
|
| 175 |
+
| 3.3004 | 8.59 | 1016000 | 3.1282 |
|
| 176 |
+
| 3.3045 | 8.66 | 1024000 | 3.1287 |
|
| 177 |
+
| 3.3045 | 8.72 | 1032000 | 3.1368 |
|
| 178 |
+
| 3.3047 | 8.79 | 1040000 | 3.1362 |
|
| 179 |
+
| 3.3047 | 8.86 | 1048000 | 3.1268 |
|
| 180 |
+
| 3.3044 | 8.93 | 1056000 | 3.1329 |
|
| 181 |
+
| 3.3044 | 8.99 | 1064000 | 3.1245 |
|
| 182 |
+
| 3.2961 | 9.06 | 1072000 | 3.1271 |
|
| 183 |
+
| 3.2961 | 9.13 | 1080000 | 3.1300 |
|
| 184 |
+
| 3.2999 | 9.2 | 1088000 | 3.1369 |
|
| 185 |
+
| 3.2999 | 9.26 | 1096000 | 3.1425 |
|
| 186 |
+
| 3.3012 | 9.33 | 1104000 | 3.1213 |
|
| 187 |
+
| 3.3012 | 9.4 | 1112000 | 3.1285 |
|
| 188 |
+
| 3.3008 | 9.47 | 1120000 | 3.1353 |
|
| 189 |
+
| 3.3008 | 9.53 | 1128000 | 3.1367 |
|
| 190 |
+
| 3.3028 | 9.6 | 1136000 | 3.1294 |
|
| 191 |
+
| 3.3028 | 9.67 | 1144000 | 3.1340 |
|
| 192 |
+
| 3.3043 | 9.74 | 1152000 | 3.1330 |
|
| 193 |
+
| 3.3043 | 9.8 | 1160000 | 3.1380 |
|
| 194 |
+
| 3.2976 | 9.87 | 1168000 | 3.1198 |
|
| 195 |
+
| 3.2976 | 9.94 | 1176000 | 3.1290 |
|
| 196 |
+
| 3.3048 | 10.01 | 1184000 | 3.1458 |
|
| 197 |
+
| 3.3048 | 10.08 | 1192000 | 3.1274 |
|
| 198 |
+
| 3.3038 | 10.14 | 1200000 | 3.1181 |
|
| 199 |
+
| 3.3038 | 10.21 | 1208000 | 3.1279 |
|
| 200 |
+
| 3.3066 | 10.28 | 1216000 | 3.1230 |
|
| 201 |
+
| 3.3066 | 10.35 | 1224000 | 3.1320 |
|
| 202 |
+
| 3.3019 | 10.41 | 1232000 | 3.1203 |
|
| 203 |
+
| 3.3019 | 10.48 | 1240000 | 3.1349 |
|
| 204 |
+
| 3.3037 | 10.55 | 1248000 | 3.1323 |
|
| 205 |
+
| 3.3037 | 10.62 | 1256000 | 3.1343 |
|
| 206 |
+
| 3.2868 | 10.68 | 1264000 | 3.1262 |
|
| 207 |
+
| 3.2868 | 10.75 | 1272000 | 3.1266 |
|
| 208 |
+
| 3.3033 | 10.82 | 1280000 | 3.1283 |
|
| 209 |
+
| 3.3033 | 10.89 | 1288000 | 3.1290 |
|
| 210 |
+
| 3.2984 | 10.95 | 1296000 | 3.1177 |
|
| 211 |
+
| 3.2984 | 11.02 | 1304000 | 3.1234 |
|
| 212 |
+
| 3.2982 | 11.09 | 1312000 | 3.1310 |
|
| 213 |
+
| 3.2982 | 11.16 | 1320000 | 3.1409 |
|
| 214 |
+
| 3.303 | 11.23 | 1328000 | 3.1330 |
|
| 215 |
+
| 3.303 | 11.29 | 1336000 | 3.1281 |
|
| 216 |
+
| 3.2976 | 11.36 | 1344000 | 3.1286 |
|
| 217 |
+
| 3.2976 | 11.43 | 1352000 | 3.1283 |
|
| 218 |
+
| 3.2923 | 11.5 | 1360000 | 3.1146 |
|
| 219 |
+
| 3.2923 | 11.56 | 1368000 | 3.1387 |
|
| 220 |
+
| 3.2988 | 11.63 | 1376000 | 3.1278 |
|
| 221 |
+
| 3.2988 | 11.7 | 1384000 | 3.1225 |
|
| 222 |
+
| 3.299 | 11.77 | 1392000 | 3.1341 |
|
| 223 |
+
| 3.299 | 11.83 | 1400000 | 3.1211 |
|
| 224 |
+
| 3.2993 | 11.9 | 1408000 | 3.1026 |
|
| 225 |
+
| 3.2993 | 11.97 | 1416000 | 3.1223 |
|
| 226 |
+
| 3.2942 | 12.04 | 1424000 | 3.1200 |
|
| 227 |
+
| 3.2942 | 12.1 | 1432000 | 3.1246 |
|
| 228 |
+
| 3.3062 | 12.17 | 1440000 | 3.1325 |
|
| 229 |
+
| 3.3062 | 12.24 | 1448000 | 3.1388 |
|
| 230 |
+
| 3.297 | 12.31 | 1456000 | 3.1371 |
|
| 231 |
+
| 3.297 | 12.37 | 1464000 | 3.1272 |
|
| 232 |
+
| 3.3033 | 12.44 | 1472000 | 3.1231 |
|
| 233 |
+
| 3.3033 | 12.51 | 1480000 | 3.1316 |
|
| 234 |
+
| 3.291 | 12.58 | 1488000 | 3.1393 |
|
| 235 |
+
| 3.291 | 12.65 | 1496000 | 3.1269 |
|
| 236 |
+
| 3.3054 | 12.71 | 1504000 | 3.1363 |
|
| 237 |
+
| 3.3054 | 12.78 | 1512000 | 3.1249 |
|
| 238 |
+
| 3.2908 | 12.85 | 1520000 | 3.1310 |
|
| 239 |
+
| 3.2908 | 12.92 | 1528000 | 3.1213 |
|
| 240 |
+
| 3.2987 | 12.98 | 1536000 | 3.1223 |
|
| 241 |
+
| 3.2987 | 13.05 | 1544000 | 3.1134 |
|
| 242 |
+
| 3.2965 | 13.12 | 1552000 | 3.1168 |
|
| 243 |
+
| 3.2965 | 13.19 | 1560000 | 3.1230 |
|
| 244 |
+
| 3.2931 | 13.25 | 1568000 | 3.1132 |
|
| 245 |
+
| 3.2931 | 13.32 | 1576000 | 3.1196 |
|
| 246 |
+
| 3.301 | 13.39 | 1584000 | 3.1287 |
|
| 247 |
+
| 3.301 | 13.46 | 1592000 | 3.1145 |
|
| 248 |
+
| 3.3004 | 13.52 | 1600000 | 3.1291 |
|
| 249 |
+
| 3.3004 | 13.59 | 1608000 | 3.1145 |
|
| 250 |
+
| 3.2992 | 13.66 | 1616000 | 3.1292 |
|
| 251 |
+
| 3.2992 | 13.73 | 1624000 | 3.1248 |
|
| 252 |
+
| 3.2974 | 13.79 | 1632000 | 3.1315 |
|
| 253 |
+
| 3.2974 | 13.86 | 1640000 | 3.1112 |
|
| 254 |
+
| 3.2993 | 13.93 | 1648000 | 3.1217 |
|
| 255 |
+
| 3.2993 | 14.0 | 1656000 | 3.1362 |
|
| 256 |
+
| 3.2934 | 14.07 | 1664000 | 3.1199 |
|
| 257 |
+
| 3.2934 | 14.13 | 1672000 | 3.1276 |
|
| 258 |
+
| 3.2964 | 14.2 | 1680000 | 3.1164 |
|
| 259 |
+
| 3.2964 | 14.27 | 1688000 | 3.1172 |
|
| 260 |
+
| 3.305 | 14.34 | 1696000 | 3.1320 |
|
| 261 |
+
| 3.305 | 14.4 | 1704000 | 3.1269 |
|
| 262 |
+
| 3.3022 | 14.47 | 1712000 | 3.1107 |
|
| 263 |
+
| 3.3022 | 14.54 | 1720000 | 3.1097 |
|
| 264 |
+
| 3.2969 | 14.61 | 1728000 | 3.1176 |
|
| 265 |
+
| 3.2969 | 14.67 | 1736000 | 3.1282 |
|
| 266 |
+
| 3.2976 | 14.74 | 1744000 | 3.1195 |
|
| 267 |
+
| 3.2976 | 14.81 | 1752000 | 3.1154 |
|
| 268 |
+
| 3.3004 | 14.88 | 1760000 | 3.1147 |
|
| 269 |
+
| 3.3004 | 14.94 | 1768000 | 3.1094 |
|
| 270 |
+
| 3.2908 | 15.01 | 1776000 | 3.1313 |
|
| 271 |
+
| 3.2908 | 15.08 | 1784000 | 3.1280 |
|
| 272 |
+
| 3.2896 | 15.15 | 1792000 | 3.1304 |
|
| 273 |
+
| 3.2896 | 15.21 | 1800000 | 3.1329 |
|
| 274 |
+
| 3.3061 | 15.28 | 1808000 | 3.1198 |
|
| 275 |
+
| 3.3061 | 15.35 | 1816000 | 3.1258 |
|
| 276 |
+
| 3.3056 | 15.42 | 1824000 | 3.1253 |
|
| 277 |
+
| 3.3056 | 15.49 | 1832000 | 3.1200 |
|
| 278 |
+
| 3.2921 | 15.55 | 1840000 | 3.1384 |
|
| 279 |
+
| 3.2921 | 15.62 | 1848000 | 3.1225 |
|
| 280 |
+
| 3.2895 | 15.69 | 1856000 | 3.1284 |
|
| 281 |
+
| 3.2895 | 15.76 | 1864000 | 3.1201 |
|
| 282 |
+
| 3.293 | 15.82 | 1872000 | 3.1256 |
|
| 283 |
+
| 3.293 | 15.89 | 1880000 | 3.1166 |
|
| 284 |
+
| 3.2963 | 15.96 | 1888000 | 3.1218 |
|
| 285 |
+
| 3.2963 | 16.03 | 1896000 | 3.1193 |
|
| 286 |
+
| 3.2908 | 16.09 | 1904000 | 3.1204 |
|
| 287 |
+
| 3.2908 | 16.16 | 1912000 | 3.1325 |
|
| 288 |
+
| 3.3039 | 16.23 | 1920000 | 3.1091 |
|
| 289 |
+
| 3.3039 | 16.3 | 1928000 | 3.1250 |
|
| 290 |
+
| 3.3011 | 16.36 | 1936000 | 3.1217 |
|
| 291 |
+
| 3.3011 | 16.43 | 1944000 | 3.1208 |
|
| 292 |
+
| 3.3003 | 16.5 | 1952000 | 3.1109 |
|
| 293 |
+
| 3.3003 | 16.57 | 1960000 | 3.1252 |
|
| 294 |
+
| 3.3012 | 16.63 | 1968000 | 3.1123 |
|
| 295 |
+
| 3.3012 | 16.7 | 1976000 | 3.1213 |
|
| 296 |
+
| 3.2885 | 16.77 | 1984000 | 3.1219 |
|
| 297 |
+
| 3.2885 | 16.84 | 1992000 | 3.1254 |
|
| 298 |
+
| 3.2982 | 16.91 | 2000000 | 3.1260 |
|
| 299 |
+
| 3.2982 | 16.97 | 2008000 | 3.1167 |
|
| 300 |
+
| 3.2962 | 17.04 | 2016000 | 3.1082 |
|
| 301 |
+
| 3.2962 | 17.11 | 2024000 | 3.1204 |
|
| 302 |
+
| 3.2889 | 17.18 | 2032000 | 3.1236 |
|
| 303 |
+
| 3.2889 | 17.24 | 2040000 | 3.1325 |
|
| 304 |
+
| 3.2892 | 17.31 | 2048000 | 3.1200 |
|
| 305 |
+
| 3.2892 | 17.38 | 2056000 | 3.1231 |
|
| 306 |
+
| 3.3028 | 17.45 | 2064000 | 3.1202 |
|
| 307 |
+
| 3.3028 | 17.51 | 2072000 | 3.1189 |
|
| 308 |
+
| 3.2889 | 17.58 | 2080000 | 3.1337 |
|
| 309 |
+
| 3.2889 | 17.65 | 2088000 | 3.1156 |
|
| 310 |
+
| 3.2985 | 17.72 | 2096000 | 3.1258 |
|
| 311 |
+
| 3.2985 | 17.78 | 2104000 | 3.1358 |
|
| 312 |
+
| 3.2949 | 17.85 | 2112000 | 3.1271 |
|
| 313 |
+
| 3.2949 | 17.92 | 2120000 | 3.1250 |
|
| 314 |
+
| 3.2987 | 17.99 | 2128000 | 3.1244 |
|
| 315 |
+
| 3.2987 | 18.05 | 2136000 | 3.1221 |
|
| 316 |
+
| 3.2884 | 18.12 | 2144000 | 3.1198 |
|
| 317 |
+
| 3.2884 | 18.19 | 2152000 | 3.1170 |
|
| 318 |
+
| 3.2918 | 18.26 | 2160000 | 3.1159 |
|
| 319 |
+
| 3.2918 | 18.33 | 2168000 | 3.1153 |
|
| 320 |
+
| 3.2995 | 18.39 | 2176000 | 3.1203 |
|
| 321 |
+
| 3.2995 | 18.46 | 2184000 | 3.1107 |
|
| 322 |
+
| 3.3003 | 18.53 | 2192000 | 3.1212 |
|
| 323 |
+
| 3.3003 | 18.6 | 2200000 | 3.1330 |
|
| 324 |
+
| 3.2921 | 18.66 | 2208000 | 3.1160 |
|
| 325 |
+
| 3.2921 | 18.73 | 2216000 | 3.1192 |
|
| 326 |
+
| 3.293 | 18.8 | 2224000 | 3.1164 |
|
| 327 |
+
| 3.293 | 18.87 | 2232000 | 3.1225 |
|
| 328 |
+
| 3.2969 | 18.93 | 2240000 | 3.1243 |
|
| 329 |
+
| 3.2969 | 19.0 | 2248000 | 3.1152 |
|
| 330 |
+
| 3.2891 | 19.07 | 2256000 | 3.1323 |
|
| 331 |
+
| 3.2891 | 19.14 | 2264000 | 3.1077 |
|
| 332 |
+
| 3.2903 | 19.2 | 2272000 | 3.1348 |
|
| 333 |
+
| 3.2903 | 19.27 | 2280000 | 3.1202 |
|
| 334 |
+
| 3.2986 | 19.34 | 2288000 | 3.1220 |
|
| 335 |
+
| 3.2986 | 19.41 | 2296000 | 3.1236 |
|
| 336 |
+
| 3.293 | 19.47 | 2304000 | 3.1224 |
|
| 337 |
+
| 3.293 | 19.54 | 2312000 | 3.1247 |
|
| 338 |
+
| 3.299 | 19.61 | 2320000 | 3.1235 |
|
| 339 |
+
| 3.299 | 19.68 | 2328000 | 3.1201 |
|
| 340 |
+
| 3.2898 | 19.75 | 2336000 | 3.1163 |
|
| 341 |
+
| 3.2898 | 19.81 | 2344000 | 3.1289 |
|
| 342 |
+
| 3.2956 | 19.88 | 2352000 | 3.1198 |
|
| 343 |
+
| 3.2956 | 19.95 | 2360000 | 3.1251 |
|
| 344 |
+
| 3.2926 | 20.02 | 2368000 | 3.1087 |
|
| 345 |
+
| 3.2926 | 20.08 | 2376000 | 3.1097 |
|
| 346 |
+
| 3.2958 | 20.15 | 2384000 | 3.1262 |
|
| 347 |
+
| 3.2958 | 20.22 | 2392000 | 3.1308 |
|
| 348 |
+
| 3.2862 | 20.29 | 2400000 | 3.1129 |
|
| 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": 20.29,
|
| 3 |
+
"eval_loss": 3.1267082691192627,
|
| 4 |
+
"eval_runtime": 105.4722,
|
| 5 |
+
"eval_samples": 99626,
|
| 6 |
+
"eval_samples_per_second": 944.571,
|
| 7 |
+
"eval_steps_per_second": 59.039,
|
| 8 |
+
"perplexity": 22.798808347164417,
|
| 9 |
+
"train_loss": 3.30909029296875,
|
| 10 |
+
"train_runtime": 182182.8159,
|
| 11 |
+
"train_samples": 1892904,
|
| 12 |
+
"train_samples_per_second": 210.777,
|
| 13 |
+
"train_steps_per_second": 13.174
|
| 14 |
+
}
|
config.json
ADDED
|
@@ -0,0 +1,28 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"_name_or_path": "cardiffnlp/twitter-roberta-base-2019-90m",
|
| 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": 20.29,
|
| 3 |
+
"eval_loss": 3.1267082691192627,
|
| 4 |
+
"eval_runtime": 105.4722,
|
| 5 |
+
"eval_samples": 99626,
|
| 6 |
+
"eval_samples_per_second": 944.571,
|
| 7 |
+
"eval_steps_per_second": 59.039,
|
| 8 |
+
"perplexity": 22.798808347164417
|
| 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 sha256:2a142e789d7350111182d89a566e05f9cf51a6f33fc795fe89c12105a3b4b86b
|
| 3 |
+
size 498859189
|
special_tokens_map.json
ADDED
|
@@ -0,0 +1,9 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"bos_token": "<s>",
|
| 3 |
+
"cls_token": "<s>",
|
| 4 |
+
"eos_token": "</s>",
|
| 5 |
+
"mask_token": "<mask>",
|
| 6 |
+
"pad_token": "<pad>",
|
| 7 |
+
"sep_token": "</s>",
|
| 8 |
+
"unk_token": "<unk>"
|
| 9 |
+
}
|
tokenizer.json
ADDED
|
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|
tokenizer_config.json
ADDED
|
@@ -0,0 +1,62 @@
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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 |
+
"bos_token": "<s>",
|
| 47 |
+
"clean_up_tokenization_spaces": true,
|
| 48 |
+
"cls_token": "<s>",
|
| 49 |
+
"eos_token": "</s>",
|
| 50 |
+
"errors": "replace",
|
| 51 |
+
"mask_token": "<mask>",
|
| 52 |
+
"max_length": 512,
|
| 53 |
+
"model_max_length": 512,
|
| 54 |
+
"pad_token": "<pad>",
|
| 55 |
+
"sep_token": "</s>",
|
| 56 |
+
"stride": 0,
|
| 57 |
+
"tokenizer_class": "RobertaTokenizer",
|
| 58 |
+
"trim_offsets": true,
|
| 59 |
+
"truncation_side": "right",
|
| 60 |
+
"truncation_strategy": "longest_first",
|
| 61 |
+
"unk_token": "<unk>"
|
| 62 |
+
}
|
train_results.json
ADDED
|
@@ -0,0 +1,8 @@
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|
| 1 |
+
{
|
| 2 |
+
"epoch": 20.29,
|
| 3 |
+
"train_loss": 3.30909029296875,
|
| 4 |
+
"train_runtime": 182182.8159,
|
| 5 |
+
"train_samples": 1892904,
|
| 6 |
+
"train_samples_per_second": 210.777,
|
| 7 |
+
"train_steps_per_second": 13.174
|
| 8 |
+
}
|
trainer_state.json
ADDED
|
@@ -0,0 +1,3328 @@
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|
| 1 |
+
{
|
| 2 |
+
"best_metric": 3.1026012897491455,
|
| 3 |
+
"best_model_checkpoint": "./model_tweets_2020_Q3_75/checkpoint-1408000",
|
| 4 |
+
"epoch": 20.28620453565723,
|
| 5 |
+
"eval_steps": 8000,
|
| 6 |
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"global_step": 2400000,
|
| 7 |
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"is_hyper_param_search": false,
|
| 8 |
+
"is_local_process_zero": true,
|
| 9 |
+
"is_world_process_zero": true,
|
| 10 |
+
"log_history": [
|
| 11 |
+
{
|
| 12 |
+
"epoch": 0.07,
|
| 13 |
+
"eval_loss": 3.451251983642578,
|
| 14 |
+
"eval_runtime": 109.3752,
|
| 15 |
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"eval_samples_per_second": 910.865,
|
| 16 |
+
"eval_steps_per_second": 56.932,
|
| 17 |
+
"step": 8000
|
| 18 |
+
},
|
| 19 |
+
{
|
| 20 |
+
"epoch": 0.14,
|
| 21 |
+
"learning_rate": 4.0726666666666665e-07,
|
| 22 |
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"loss": 3.6645,
|
| 23 |
+
"step": 16000
|
| 24 |
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},
|
| 25 |
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{
|
| 26 |
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"epoch": 0.14,
|
| 27 |
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"eval_loss": 3.379037380218506,
|
| 28 |
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"eval_runtime": 110.7092,
|
| 29 |
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"eval_samples_per_second": 899.889,
|
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training_args.bin
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vocab.json
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