--- license: mit base_model: haryoaw/scenario-TCR_data-cardiffnlp_tweet_sentiment_multilingual_all_a tags: - generated_from_trainer datasets: - tweet_sentiment_multilingual metrics: - accuracy - f1 model-index: - name: scenario-KD-PO-CDF-ALL-D2_data-cardiffnlp_tweet_sentiment_multilingual_all_delta results: [] --- # scenario-KD-PO-CDF-ALL-D2_data-cardiffnlp_tweet_sentiment_multilingual_all_delta This model is a fine-tuned version of [haryoaw/scenario-TCR_data-cardiffnlp_tweet_sentiment_multilingual_all_a](https://huggingface.co/haryoaw/scenario-TCR_data-cardiffnlp_tweet_sentiment_multilingual_all_a) on the tweet_sentiment_multilingual dataset. It achieves the following results on the evaluation set: - Loss: 3.3760 - Accuracy: 0.5586 - F1: 0.5590 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 32 - eval_batch_size: 32 - seed: 7777 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 50 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:| | 4.88 | 1.09 | 500 | 4.1661 | 0.4518 | 0.4462 | | 3.9513 | 2.17 | 1000 | 3.7172 | 0.5154 | 0.5102 | | 3.4556 | 3.26 | 1500 | 3.5612 | 0.5293 | 0.5221 | | 3.0959 | 4.35 | 2000 | 3.5271 | 0.5440 | 0.5349 | | 2.7593 | 5.43 | 2500 | 3.3105 | 0.5602 | 0.5595 | | 2.548 | 6.52 | 3000 | 3.4842 | 0.5355 | 0.5360 | | 2.3323 | 7.61 | 3500 | 3.2883 | 0.5575 | 0.5444 | | 2.1215 | 8.7 | 4000 | 3.2282 | 0.5583 | 0.5607 | | 1.9719 | 9.78 | 4500 | 3.5734 | 0.5594 | 0.5534 | | 1.8238 | 10.87 | 5000 | 3.2866 | 0.5552 | 0.5538 | | 1.703 | 11.96 | 5500 | 3.2345 | 0.5556 | 0.5557 | | 1.5931 | 13.04 | 6000 | 3.2219 | 0.5583 | 0.5539 | | 1.4959 | 14.13 | 6500 | 3.3073 | 0.5637 | 0.5644 | | 1.4198 | 15.22 | 7000 | 3.5221 | 0.5579 | 0.5541 | | 1.35 | 16.3 | 7500 | 3.5125 | 0.5660 | 0.5643 | | 1.2937 | 17.39 | 8000 | 3.5089 | 0.5640 | 0.5637 | | 1.2282 | 18.48 | 8500 | 3.4262 | 0.5664 | 0.5658 | | 1.1698 | 19.57 | 9000 | 3.3739 | 0.5598 | 0.5593 | | 1.1402 | 20.65 | 9500 | 3.4930 | 0.5521 | 0.5541 | | 1.0874 | 21.74 | 10000 | 3.4935 | 0.5625 | 0.5602 | | 1.0652 | 22.83 | 10500 | 3.3963 | 0.5482 | 0.5478 | | 1.0191 | 23.91 | 11000 | 3.4823 | 0.5571 | 0.5583 | | 0.9868 | 25.0 | 11500 | 3.6035 | 0.5579 | 0.5586 | | 0.9487 | 26.09 | 12000 | 3.6034 | 0.5525 | 0.5488 | | 0.936 | 27.17 | 12500 | 3.5428 | 0.5556 | 0.5542 | | 0.9116 | 28.26 | 13000 | 3.6023 | 0.5532 | 0.5509 | | 0.8868 | 29.35 | 13500 | 3.5292 | 0.5579 | 0.5581 | | 0.8733 | 30.43 | 14000 | 3.4206 | 0.5594 | 0.5589 | | 0.8538 | 31.52 | 14500 | 3.4417 | 0.5594 | 0.5592 | | 0.8289 | 32.61 | 15000 | 3.4970 | 0.5579 | 0.5584 | | 0.823 | 33.7 | 15500 | 3.4860 | 0.5625 | 0.5617 | | 0.7992 | 34.78 | 16000 | 3.5193 | 0.5671 | 0.5659 | | 0.7974 | 35.87 | 16500 | 3.3709 | 0.5490 | 0.5497 | | 0.7775 | 36.96 | 17000 | 3.3854 | 0.5706 | 0.5720 | | 0.7691 | 38.04 | 17500 | 3.3827 | 0.5698 | 0.5700 | | 0.758 | 39.13 | 18000 | 3.4608 | 0.5818 | 0.5818 | | 0.757 | 40.22 | 18500 | 3.3860 | 0.5683 | 0.5681 | | 0.7481 | 41.3 | 19000 | 3.3757 | 0.5687 | 0.5686 | | 0.7387 | 42.39 | 19500 | 3.4830 | 0.5714 | 0.5707 | | 0.7276 | 43.48 | 20000 | 3.3942 | 0.5617 | 0.5611 | | 0.7279 | 44.57 | 20500 | 3.3357 | 0.5725 | 0.5726 | | 0.7127 | 45.65 | 21000 | 3.3856 | 0.5521 | 0.5523 | | 0.7148 | 46.74 | 21500 | 3.4401 | 0.5660 | 0.5673 | | 0.7219 | 47.83 | 22000 | 3.4684 | 0.5629 | 0.5627 | | 0.7005 | 48.91 | 22500 | 3.3840 | 0.5625 | 0.5631 | | 0.7114 | 50.0 | 23000 | 3.3760 | 0.5586 | 0.5590 | ### Framework versions - Transformers 4.33.3 - Pytorch 2.1.1+cu121 - Datasets 2.14.5 - Tokenizers 0.13.3