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--- |
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license: mit |
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base_model: FacebookAI/xlm-roberta-base |
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tags: |
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- generated_from_trainer |
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datasets: |
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- tweet_sentiment_multilingual |
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metrics: |
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- accuracy |
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- f1 |
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model-index: |
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- name: scenario-KD-PR-CDF-ALL-D2_data-cardiffnlp_tweet_sentiment_multilingual_all_gamma |
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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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# scenario-KD-PR-CDF-ALL-D2_data-cardiffnlp_tweet_sentiment_multilingual_all_gamma |
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This model is a fine-tuned version of [FacebookAI/xlm-roberta-base](https://huggingface.co/FacebookAI/xlm-roberta-base) on the tweet_sentiment_multilingual dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.4838 |
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- Accuracy: 0.5505 |
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- F1: 0.5508 |
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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: 5e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 88458 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 50 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:| |
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| 4.8911 | 1.09 | 500 | 4.3088 | 0.4047 | 0.3809 | |
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| 4.106 | 2.17 | 1000 | 3.7773 | 0.5058 | 0.4920 | |
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| 3.4954 | 3.26 | 1500 | 3.3608 | 0.5347 | 0.5357 | |
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| 3.1472 | 4.35 | 2000 | 3.4225 | 0.5343 | 0.5327 | |
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| 2.8094 | 5.43 | 2500 | 3.4088 | 0.5436 | 0.5399 | |
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| 2.5414 | 6.52 | 3000 | 3.3362 | 0.5552 | 0.5562 | |
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| 2.331 | 7.61 | 3500 | 3.3218 | 0.5459 | 0.5389 | |
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| 2.1295 | 8.7 | 4000 | 3.6107 | 0.5525 | 0.5532 | |
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| 1.9843 | 9.78 | 4500 | 3.4533 | 0.5575 | 0.5578 | |
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| 1.8472 | 10.87 | 5000 | 3.2933 | 0.5482 | 0.5469 | |
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| 1.7227 | 11.96 | 5500 | 3.3387 | 0.5513 | 0.5521 | |
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| 1.6067 | 13.04 | 6000 | 3.2725 | 0.5444 | 0.5454 | |
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| 1.5328 | 14.13 | 6500 | 3.3817 | 0.5513 | 0.5528 | |
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| 1.4166 | 15.22 | 7000 | 3.5382 | 0.5421 | 0.5437 | |
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| 1.346 | 16.3 | 7500 | 3.4353 | 0.5567 | 0.5574 | |
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| 1.3038 | 17.39 | 8000 | 3.5873 | 0.5478 | 0.5462 | |
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| 1.2285 | 18.48 | 8500 | 3.7322 | 0.5525 | 0.5516 | |
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| 1.1916 | 19.57 | 9000 | 3.5055 | 0.5486 | 0.5488 | |
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| 1.1143 | 20.65 | 9500 | 3.4413 | 0.5575 | 0.5589 | |
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| 1.0749 | 21.74 | 10000 | 3.7211 | 0.5559 | 0.5572 | |
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| 1.0668 | 22.83 | 10500 | 3.5802 | 0.5575 | 0.5576 | |
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| 1.0111 | 23.91 | 11000 | 3.5038 | 0.5606 | 0.5598 | |
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| 0.9837 | 25.0 | 11500 | 3.6704 | 0.5521 | 0.5517 | |
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| 0.9643 | 26.09 | 12000 | 3.5238 | 0.5598 | 0.5609 | |
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| 0.9311 | 27.17 | 12500 | 3.5195 | 0.5559 | 0.5558 | |
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| 0.902 | 28.26 | 13000 | 3.3760 | 0.5679 | 0.5653 | |
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| 0.8935 | 29.35 | 13500 | 3.6155 | 0.5536 | 0.5539 | |
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| 0.8745 | 30.43 | 14000 | 3.5108 | 0.5667 | 0.5662 | |
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| 0.8444 | 31.52 | 14500 | 3.6231 | 0.5606 | 0.5597 | |
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| 0.8327 | 32.61 | 15000 | 3.5783 | 0.5552 | 0.5508 | |
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| 0.8237 | 33.7 | 15500 | 3.5527 | 0.5556 | 0.5548 | |
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| 0.8035 | 34.78 | 16000 | 3.4553 | 0.5660 | 0.5657 | |
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| 0.7948 | 35.87 | 16500 | 3.4230 | 0.5490 | 0.5503 | |
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| 0.7886 | 36.96 | 17000 | 3.5010 | 0.5482 | 0.5494 | |
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| 0.7711 | 38.04 | 17500 | 3.4771 | 0.5644 | 0.5648 | |
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| 0.76 | 39.13 | 18000 | 3.5514 | 0.5563 | 0.5570 | |
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| 0.7509 | 40.22 | 18500 | 3.4726 | 0.5586 | 0.5585 | |
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| 0.7522 | 41.3 | 19000 | 3.5237 | 0.5606 | 0.5586 | |
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| 0.7368 | 42.39 | 19500 | 3.4514 | 0.5532 | 0.5516 | |
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| 0.7377 | 43.48 | 20000 | 3.5320 | 0.5633 | 0.5636 | |
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| 0.7142 | 44.57 | 20500 | 3.4685 | 0.5613 | 0.5608 | |
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| 0.7255 | 45.65 | 21000 | 3.4919 | 0.5652 | 0.5635 | |
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| 0.7139 | 46.74 | 21500 | 3.4869 | 0.5556 | 0.5551 | |
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| 0.7124 | 47.83 | 22000 | 3.4748 | 0.5644 | 0.5642 | |
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| 0.7065 | 48.91 | 22500 | 3.4405 | 0.5602 | 0.5601 | |
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| 0.7038 | 50.0 | 23000 | 3.4838 | 0.5505 | 0.5508 | |
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### Framework versions |
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- Transformers 4.33.3 |
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- Pytorch 2.1.1+cu121 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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