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2020-Q3-full_tweets

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roberta
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+ ---
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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-full_tweets
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+ results: []
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+ ---
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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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+
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+ # 2020-Q3-full_tweets
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+
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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: 1.9142
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 32
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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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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:-----:|:-------:|:---------------:|
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+ | No log | 0.03 | 8000 | 2.2197 |
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+ | 2.3934 | 0.07 | 16000 | 2.1429 |
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+ | 2.3934 | 0.1 | 24000 | 2.1001 |
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+ | 2.2294 | 0.13 | 32000 | 2.0762 |
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+ | 2.2294 | 0.17 | 40000 | 2.0515 |
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+ | 2.1835 | 0.2 | 48000 | 2.0435 |
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+ | 2.1835 | 0.24 | 56000 | 2.0346 |
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+ | 2.1517 | 0.27 | 64000 | 2.0254 |
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+ | 2.1517 | 0.3 | 72000 | 2.0175 |
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+ | 2.1381 | 0.34 | 80000 | 2.0077 |
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+ | 2.1381 | 0.37 | 88000 | 2.0029 |
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+ | 2.1244 | 0.4 | 96000 | 2.0011 |
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+ | 2.1244 | 0.44 | 104000 | 1.9980 |
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+ | 2.1116 | 0.47 | 112000 | 1.9901 |
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+ | 2.1116 | 0.51 | 120000 | 1.9840 |
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+ | 2.1104 | 0.54 | 128000 | 1.9885 |
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+ | 2.1104 | 0.57 | 136000 | 1.9855 |
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+ | 2.1031 | 0.61 | 144000 | 1.9829 |
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+ | 2.1031 | 0.64 | 152000 | 1.9813 |
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+ | 2.0971 | 0.67 | 160000 | 1.9812 |
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+ | 2.0971 | 0.71 | 168000 | 1.9795 |
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+ | 2.1044 | 0.74 | 176000 | 1.9738 |
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+ | 2.1044 | 0.77 | 184000 | 1.9768 |
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+ | 2.0928 | 0.81 | 192000 | 1.9786 |
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+ | 2.0928 | 0.84 | 200000 | 1.9699 |
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+ | 2.0949 | 0.88 | 208000 | 1.9700 |
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+ | 2.0949 | 0.91 | 216000 | 1.9653 |
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+ | 2.0892 | 0.94 | 224000 | 1.9681 |
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+ | 2.0892 | 0.98 | 232000 | 1.9650 |
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+ | 2.0841 | 1.01 | 240000 | 1.9638 |
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+ | 2.0841 | 1.04 | 248000 | 1.9682 |
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+ | 2.0887 | 1.08 | 256000 | 1.9605 |
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+ | 2.0887 | 1.11 | 264000 | 1.9614 |
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+ | 2.0842 | 1.15 | 272000 | 1.9624 |
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+ | 2.0842 | 1.18 | 280000 | 1.9605 |
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+ | 2.0773 | 1.21 | 288000 | 1.9554 |
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+ | 2.0773 | 1.25 | 296000 | 1.9578 |
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+ | 2.0795 | 1.28 | 304000 | 1.9572 |
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+ | 2.0795 | 1.31 | 312000 | 1.9521 |
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+ | 2.0794 | 1.35 | 320000 | 1.9551 |
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+ | 2.0794 | 1.38 | 328000 | 1.9569 |
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+ | 2.0788 | 1.41 | 336000 | 1.9571 |
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+ | 2.0788 | 1.45 | 344000 | 1.9502 |
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+ | 2.0778 | 1.48 | 352000 | 1.9544 |
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+ | 2.0778 | 1.52 | 360000 | 1.9470 |
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+ | 2.0694 | 1.55 | 368000 | 1.9545 |
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+ | 2.0694 | 1.58 | 376000 | 1.9472 |
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+ | 2.0718 | 1.62 | 384000 | 1.9477 |
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+ | 2.0718 | 1.65 | 392000 | 1.9496 |
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+ | 2.0787 | 1.68 | 400000 | 1.9440 |
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+ | 2.0787 | 1.72 | 408000 | 1.9484 |
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+ | 2.0764 | 1.75 | 416000 | 1.9475 |
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+ | 2.0764 | 1.79 | 424000 | 1.9469 |
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+ | 2.0795 | 1.82 | 432000 | 1.9474 |
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+ | 2.0795 | 1.85 | 440000 | 1.9492 |
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+ | 2.07 | 1.89 | 448000 | 1.9480 |
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+ | 2.07 | 1.92 | 456000 | 1.9482 |
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+ | 2.0712 | 1.95 | 464000 | 1.9498 |
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+ | 2.0712 | 1.99 | 472000 | 1.9429 |
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+ | 2.0739 | 2.02 | 480000 | 1.9456 |
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+ | 2.0739 | 2.05 | 488000 | 1.9469 |
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+ | 2.0688 | 2.09 | 496000 | 1.9467 |
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+ | 2.0688 | 2.12 | 504000 | 1.9454 |
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+ | 2.0706 | 2.16 | 512000 | 1.9440 |
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+ | 2.0706 | 2.19 | 520000 | 1.9401 |
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+ | 2.0694 | 2.22 | 528000 | 1.9397 |
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+ | 2.0694 | 2.26 | 536000 | 1.9429 |
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+ | 2.0698 | 2.29 | 544000 | 1.9484 |
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+ | 2.0698 | 2.32 | 552000 | 1.9375 |
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+ | 2.0681 | 2.36 | 560000 | 1.9411 |
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+ | 2.0681 | 2.39 | 568000 | 1.9419 |
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+ | 2.0676 | 2.43 | 576000 | 1.9373 |
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+ | 2.0676 | 2.46 | 584000 | 1.9366 |
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+ | 2.0641 | 2.49 | 592000 | 1.9422 |
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+ | 2.0641 | 2.53 | 600000 | 1.9365 |
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+ | 2.0692 | 2.56 | 608000 | 1.9417 |
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+ | 2.0692 | 2.59 | 616000 | 1.9385 |
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+ | 2.0676 | 2.63 | 624000 | 1.9362 |
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+ | 2.0676 | 2.66 | 632000 | 1.9414 |
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+ | 2.0657 | 2.69 | 640000 | 1.9437 |
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+ | 2.0657 | 2.73 | 648000 | 1.9356 |
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+ | 2.0638 | 2.76 | 656000 | 1.9353 |
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+ | 2.0638 | 2.8 | 664000 | 1.9385 |
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+ | 2.0673 | 2.83 | 672000 | 1.9359 |
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+ | 2.0673 | 2.86 | 680000 | 1.9314 |
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+ | 2.0634 | 2.9 | 688000 | 1.9294 |
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+ | 2.0634 | 2.93 | 696000 | 1.9346 |
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+ | 2.0643 | 2.96 | 704000 | 1.9335 |
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+ | 2.0643 | 3.0 | 712000 | 1.9316 |
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+ | 2.0596 | 3.03 | 720000 | 1.9356 |
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+ | 2.0596 | 3.07 | 728000 | 1.9390 |
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+ | 2.0637 | 3.1 | 736000 | 1.9397 |
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+ | 2.0637 | 3.13 | 744000 | 1.9375 |
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+ | 2.0637 | 3.17 | 752000 | 1.9352 |
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+ | 2.0637 | 3.2 | 760000 | 1.9310 |
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+ | 2.0681 | 3.23 | 768000 | 1.9316 |
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+ | 2.0681 | 3.27 | 776000 | 1.9269 |
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+ | 2.0663 | 3.3 | 784000 | 1.9301 |
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+ | 2.0663 | 3.33 | 792000 | 1.9354 |
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+ | 2.0653 | 3.37 | 800000 | 1.9373 |
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+ | 2.0653 | 3.4 | 808000 | 1.9354 |
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+ | 2.0606 | 3.44 | 816000 | 1.9286 |
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+ | 2.0606 | 3.47 | 824000 | 1.9318 |
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+ | 2.0601 | 3.5 | 832000 | 1.9287 |
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+ | 2.0601 | 3.54 | 840000 | 1.9280 |
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+ | 2.0555 | 3.57 | 848000 | 1.9279 |
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+ | 2.0555 | 3.6 | 856000 | 1.9297 |
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+ | 2.0561 | 3.64 | 864000 | 1.9290 |
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+ | 2.0561 | 3.67 | 872000 | 1.9252 |
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+ | 2.066 | 3.71 | 880000 | 1.9274 |
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+ | 2.066 | 3.74 | 888000 | 1.9257 |
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+ | 2.0634 | 3.77 | 896000 | 1.9290 |
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+ | 2.0634 | 3.81 | 904000 | 1.9267 |
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+ | 2.0613 | 3.84 | 912000 | 1.9295 |
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+ | 2.0613 | 3.87 | 920000 | 1.9300 |
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+ | 2.0599 | 3.91 | 928000 | 1.9326 |
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+ | 2.0599 | 3.94 | 936000 | 1.9313 |
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+ | 2.0592 | 3.97 | 944000 | 1.9237 |
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+ | 2.0592 | 4.01 | 952000 | 1.9272 |
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+ | 2.0602 | 4.04 | 960000 | 1.9261 |
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+ | 2.0602 | 4.08 | 968000 | 1.9283 |
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+ | 2.0575 | 4.11 | 976000 | 1.9294 |
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+ | 2.0575 | 4.14 | 984000 | 1.9284 |
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+ | 2.0585 | 4.18 | 992000 | 1.9263 |
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+ | 2.0585 | 4.21 | 1000000 | 1.9227 |
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+ | 2.0535 | 4.24 | 1008000 | 1.9251 |
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+ | 2.0535 | 4.28 | 1016000 | 1.9273 |
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+ | 2.062 | 4.31 | 1024000 | 1.9242 |
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+ | 2.062 | 4.35 | 1032000 | 1.9242 |
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+ | 2.0606 | 4.38 | 1040000 | 1.9255 |
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+ | 2.0606 | 4.41 | 1048000 | 1.9233 |
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+ | 2.0565 | 4.45 | 1056000 | 1.9243 |
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+ | 2.0565 | 4.48 | 1064000 | 1.9272 |
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+ | 2.0538 | 4.51 | 1072000 | 1.9308 |
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+ | 2.0538 | 4.55 | 1080000 | 1.9236 |
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+ | 2.0573 | 4.58 | 1088000 | 1.9246 |
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+ | 2.0573 | 4.61 | 1096000 | 1.9237 |
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+ | 2.0562 | 4.65 | 1104000 | 1.9199 |
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+ | 2.0562 | 4.68 | 1112000 | 1.9235 |
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+ | 2.0534 | 4.72 | 1120000 | 1.9209 |
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+ | 2.0534 | 4.75 | 1128000 | 1.9215 |
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+ | 2.0567 | 4.78 | 1136000 | 1.9242 |
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+ | 2.0567 | 4.82 | 1144000 | 1.9272 |
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+ | 2.0592 | 4.85 | 1152000 | 1.9257 |
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+ | 2.0592 | 4.88 | 1160000 | 1.9228 |
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+ | 2.0599 | 4.92 | 1168000 | 1.9205 |
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+ | 2.0599 | 4.95 | 1176000 | 1.9190 |
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+ | 2.0504 | 4.99 | 1184000 | 1.9241 |
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+ | 2.0504 | 5.02 | 1192000 | 1.9214 |
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+ | 2.0541 | 5.05 | 1200000 | 1.9265 |
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+ | 2.0541 | 5.09 | 1208000 | 1.9250 |
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+ | 2.0581 | 5.12 | 1216000 | 1.9174 |
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+ | 2.0581 | 5.15 | 1224000 | 1.9232 |
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+ | 2.057 | 5.19 | 1232000 | 1.9242 |
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+ | 2.057 | 5.22 | 1240000 | 1.9201 |
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+ | 2.0541 | 5.25 | 1248000 | 1.9187 |
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+ | 2.0541 | 5.29 | 1256000 | 1.9205 |
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+ | 2.0542 | 5.32 | 1264000 | 1.9178 |
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+ | 2.0542 | 5.36 | 1272000 | 1.9239 |
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+ | 2.0526 | 5.39 | 1280000 | 1.9185 |
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+ | 2.0526 | 5.42 | 1288000 | 1.9227 |
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+ | 2.0503 | 5.46 | 1296000 | 1.9223 |
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+ | 2.0503 | 5.49 | 1304000 | 1.9230 |
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+ | 2.0579 | 5.52 | 1312000 | 1.9143 |
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+ | 2.0579 | 5.56 | 1320000 | 1.9188 |
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+ | 2.0523 | 5.59 | 1328000 | 1.9170 |
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+ | 2.0523 | 5.63 | 1336000 | 1.9252 |
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+ | 2.056 | 5.66 | 1344000 | 1.9183 |
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+ | 2.056 | 5.69 | 1352000 | 1.9237 |
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+ | 2.0545 | 5.73 | 1360000 | 1.9198 |
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+ | 2.0545 | 5.76 | 1368000 | 1.9225 |
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+ | 2.0552 | 5.79 | 1376000 | 1.9172 |
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+ | 2.0552 | 5.83 | 1384000 | 1.9179 |
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+ | 2.0571 | 5.86 | 1392000 | 1.9238 |
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+ | 2.0571 | 5.89 | 1400000 | 1.9189 |
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+ | 2.0637 | 5.93 | 1408000 | 1.9217 |
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+ | 2.0637 | 5.96 | 1416000 | 1.9190 |
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+ | 2.0554 | 6.0 | 1424000 | 1.9259 |
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+ | 2.0554 | 6.03 | 1432000 | 1.9184 |
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+ | 2.0545 | 6.06 | 1440000 | 1.9244 |
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+ | 2.0545 | 6.1 | 1448000 | 1.9201 |
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+ | 2.0538 | 6.13 | 1456000 | 1.9251 |
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+ | 2.0538 | 6.16 | 1464000 | 1.9216 |
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+ | 2.058 | 6.2 | 1472000 | 1.9221 |
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+ | 2.058 | 6.23 | 1480000 | 1.9247 |
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+ | 2.0482 | 6.27 | 1488000 | 1.9209 |
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+ | 2.0482 | 6.3 | 1496000 | 1.9207 |
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+ | 2.0528 | 6.33 | 1504000 | 1.9177 |
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+ | 2.0528 | 6.37 | 1512000 | 1.9141 |
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+ | 2.0529 | 6.4 | 1520000 | 1.9213 |
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+ | 2.0529 | 6.43 | 1528000 | 1.9170 |
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+ | 2.059 | 6.47 | 1536000 | 1.9161 |
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+ | 2.059 | 6.5 | 1544000 | 1.9164 |
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+ | 2.056 | 6.53 | 1552000 | 1.9177 |
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+ | 2.056 | 6.57 | 1560000 | 1.9189 |
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+ | 2.058 | 6.6 | 1568000 | 1.9181 |
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+ | 2.058 | 6.64 | 1576000 | 1.9214 |
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+ | 2.0543 | 6.67 | 1584000 | 1.9137 |
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+ | 2.0543 | 6.7 | 1592000 | 1.9181 |
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+ | 2.0513 | 6.74 | 1600000 | 1.9187 |
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+ | 2.0513 | 6.77 | 1608000 | 1.9176 |
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+ | 2.0587 | 6.8 | 1616000 | 1.9145 |
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+ | 2.0587 | 6.84 | 1624000 | 1.9192 |
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+ | 2.053 | 6.87 | 1632000 | 1.9202 |
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+ | 2.053 | 6.91 | 1640000 | 1.9183 |
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+ | 2.0543 | 6.94 | 1648000 | 1.9163 |
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+ | 2.0543 | 6.97 | 1656000 | 1.9171 |
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+ | 2.0492 | 7.01 | 1664000 | 1.9183 |
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+ | 2.0492 | 7.04 | 1672000 | 1.9172 |
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+ | 2.0505 | 7.07 | 1680000 | 1.9190 |
259
+ | 2.0505 | 7.11 | 1688000 | 1.9181 |
260
+ | 2.0548 | 7.14 | 1696000 | 1.9160 |
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+ | 2.0548 | 7.17 | 1704000 | 1.9168 |
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+ | 2.0524 | 7.21 | 1712000 | 1.9155 |
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+ | 2.0524 | 7.24 | 1720000 | 1.9161 |
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+ | 2.0539 | 7.28 | 1728000 | 1.9189 |
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+ | 2.0539 | 7.31 | 1736000 | 1.9169 |
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+ | 2.0542 | 7.34 | 1744000 | 1.9177 |
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+ | 2.0542 | 7.38 | 1752000 | 1.9140 |
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+ | 2.0509 | 7.41 | 1760000 | 1.9152 |
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+ | 2.0509 | 7.44 | 1768000 | 1.9160 |
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+ | 2.0507 | 7.48 | 1776000 | 1.9156 |
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+ | 2.0507 | 7.51 | 1784000 | 1.9139 |
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+ | 2.057 | 7.55 | 1792000 | 1.9140 |
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+ | 2.057 | 7.58 | 1800000 | 1.9248 |
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+ | 2.0515 | 7.61 | 1808000 | 1.9143 |
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+ | 2.0515 | 7.65 | 1816000 | 1.9188 |
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+ | 2.0503 | 7.68 | 1824000 | 1.9127 |
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+ | 2.0503 | 7.71 | 1832000 | 1.9132 |
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+ | 2.0534 | 7.75 | 1840000 | 1.9129 |
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+ | 2.0534 | 7.78 | 1848000 | 1.9195 |
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+ | 2.0553 | 7.81 | 1856000 | 1.9157 |
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+ | 2.0553 | 7.85 | 1864000 | 1.9177 |
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+ | 2.0496 | 7.88 | 1872000 | 1.9148 |
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+ | 2.0496 | 7.92 | 1880000 | 1.9132 |
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+ | 2.0537 | 7.95 | 1888000 | 1.9184 |
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+ | 2.0537 | 7.98 | 1896000 | 1.9160 |
286
+ | 2.0505 | 8.02 | 1904000 | 1.9151 |
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+ | 2.0505 | 8.05 | 1912000 | 1.9210 |
288
+ | 2.0536 | 8.08 | 1920000 | 1.9173 |
289
+ | 2.0536 | 8.12 | 1928000 | 1.9139 |
290
+ | 2.0493 | 8.15 | 1936000 | 1.9209 |
291
+ | 2.0493 | 8.19 | 1944000 | 1.9151 |
292
+ | 2.052 | 8.22 | 1952000 | 1.9174 |
293
+ | 2.052 | 8.25 | 1960000 | 1.9146 |
294
+ | 2.0575 | 8.29 | 1968000 | 1.9169 |
295
+ | 2.0575 | 8.32 | 1976000 | 1.9173 |
296
+ | 2.0499 | 8.35 | 1984000 | 1.9175 |
297
+ | 2.0499 | 8.39 | 1992000 | 1.9136 |
298
+ | 2.0573 | 8.42 | 2000000 | 1.9159 |
299
+ | 2.0573 | 8.45 | 2008000 | 1.9148 |
300
+ | 2.0556 | 8.49 | 2016000 | 1.9174 |
301
+ | 2.0556 | 8.52 | 2024000 | 1.9146 |
302
+ | 2.0558 | 8.56 | 2032000 | 1.9152 |
303
+ | 2.0558 | 8.59 | 2040000 | 1.9125 |
304
+ | 2.0493 | 8.62 | 2048000 | 1.9156 |
305
+ | 2.0493 | 8.66 | 2056000 | 1.9121 |
306
+ | 2.0492 | 8.69 | 2064000 | 1.9227 |
307
+ | 2.0492 | 8.72 | 2072000 | 1.9136 |
308
+ | 2.0576 | 8.76 | 2080000 | 1.9147 |
309
+ | 2.0576 | 8.79 | 2088000 | 1.9159 |
310
+ | 2.0512 | 8.83 | 2096000 | 1.9116 |
311
+ | 2.0512 | 8.86 | 2104000 | 1.9159 |
312
+ | 2.05 | 8.89 | 2112000 | 1.9130 |
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+ | 2.05 | 8.93 | 2120000 | 1.9152 |
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+ | 2.0437 | 8.96 | 2128000 | 1.9176 |
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+ | 2.0437 | 8.99 | 2136000 | 1.9193 |
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+ | 2.053 | 9.03 | 2144000 | 1.9124 |
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+ | 2.053 | 9.06 | 2152000 | 1.9139 |
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+ | 2.0496 | 9.09 | 2160000 | 1.9128 |
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+ | 2.0496 | 9.13 | 2168000 | 1.9162 |
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+ | 2.0495 | 9.16 | 2176000 | 1.9065 |
321
+ | 2.0495 | 9.2 | 2184000 | 1.9211 |
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+ | 2.0468 | 9.23 | 2192000 | 1.9095 |
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+ | 2.0468 | 9.26 | 2200000 | 1.9163 |
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+ | 2.0507 | 9.3 | 2208000 | 1.9106 |
325
+ | 2.0507 | 9.33 | 2216000 | 1.9165 |
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+ | 2.0526 | 9.36 | 2224000 | 1.9179 |
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+ | 2.0526 | 9.4 | 2232000 | 1.9178 |
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+ | 2.0537 | 9.43 | 2240000 | 1.9163 |
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+ | 2.0537 | 9.47 | 2248000 | 1.9159 |
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+ | 2.0502 | 9.5 | 2256000 | 1.9146 |
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+ | 2.0502 | 9.53 | 2264000 | 1.9169 |
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+ | 2.0492 | 9.57 | 2272000 | 1.9164 |
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+ | 2.0492 | 9.6 | 2280000 | 1.9154 |
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+ | 2.0505 | 9.63 | 2288000 | 1.9066 |
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+ | 2.0505 | 9.67 | 2296000 | 1.9140 |
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+ | 2.0516 | 9.7 | 2304000 | 1.9125 |
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+ | 2.0516 | 9.73 | 2312000 | 1.9184 |
338
+ | 2.0559 | 9.77 | 2320000 | 1.9178 |
339
+ | 2.0559 | 9.8 | 2328000 | 1.9164 |
340
+ | 2.0528 | 9.84 | 2336000 | 1.9087 |
341
+ | 2.0528 | 9.87 | 2344000 | 1.9165 |
342
+ | 2.0559 | 9.9 | 2352000 | 1.9113 |
343
+ | 2.0559 | 9.94 | 2360000 | 1.9146 |
344
+ | 2.058 | 9.97 | 2368000 | 1.9156 |
345
+ | 2.058 | 10.0 | 2376000 | 1.9137 |
346
+ | 2.053 | 10.04 | 2384000 | 1.9081 |
347
+ | 2.053 | 10.07 | 2392000 | 1.9148 |
348
+ | 2.0566 | 10.11 | 2400000 | 1.9142 |
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
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