--- license: mit base_model: haryoaw/scenario-MDBT-TCR_data-cardiffnlp_tweet_sentiment_multilingual_all tags: - generated_from_trainer datasets: - tweet_sentiment_multilingual metrics: - accuracy - f1 model-index: - name: scenario-KD-PR-CDF-ALL-D2_data-cardiffnlp_tweet_sentiment_multilingual_all66 results: [] --- # scenario-KD-PR-CDF-ALL-D2_data-cardiffnlp_tweet_sentiment_multilingual_all66 This model is a fine-tuned version of [haryoaw/scenario-MDBT-TCR_data-cardiffnlp_tweet_sentiment_multilingual_all](https://huggingface.co/haryoaw/scenario-MDBT-TCR_data-cardiffnlp_tweet_sentiment_multilingual_all) on the tweet_sentiment_multilingual dataset. It achieves the following results on the evaluation set: - Loss: 1.2134 - Accuracy: 0.5976 - F1: 0.5983 ## 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: 66 - 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 | |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:| | 1.2324 | 1.09 | 500 | 1.1970 | 0.5390 | 0.5349 | | 1.1375 | 2.17 | 1000 | 1.1962 | 0.5683 | 0.5697 | | 1.0818 | 3.26 | 1500 | 1.2071 | 0.5864 | 0.5880 | | 1.0336 | 4.35 | 2000 | 1.2252 | 0.5829 | 0.5784 | | 0.9993 | 5.43 | 2500 | 1.2483 | 0.5718 | 0.5739 | | 0.9736 | 6.52 | 3000 | 1.2370 | 0.5679 | 0.5704 | | 0.9561 | 7.61 | 3500 | 1.2357 | 0.5787 | 0.5793 | | 0.9417 | 8.7 | 4000 | 1.2761 | 0.5575 | 0.5567 | | 0.9318 | 9.78 | 4500 | 1.2588 | 0.5752 | 0.5752 | | 0.9229 | 10.87 | 5000 | 1.2304 | 0.5748 | 0.5759 | | 0.9148 | 11.96 | 5500 | 1.2564 | 0.5741 | 0.5759 | | 0.9085 | 13.04 | 6000 | 1.2593 | 0.5714 | 0.5695 | | 0.9053 | 14.13 | 6500 | 1.2399 | 0.5694 | 0.5694 | | 0.8993 | 15.22 | 7000 | 1.2473 | 0.5702 | 0.5710 | | 0.898 | 16.3 | 7500 | 1.2271 | 0.5787 | 0.5800 | | 0.8894 | 17.39 | 8000 | 1.2384 | 0.5691 | 0.5686 | | 0.8894 | 18.48 | 8500 | 1.2441 | 0.5660 | 0.5669 | | 0.8853 | 19.57 | 9000 | 1.2530 | 0.5725 | 0.5741 | | 0.8828 | 20.65 | 9500 | 1.2464 | 0.5698 | 0.5712 | | 0.8785 | 21.74 | 10000 | 1.2423 | 0.5860 | 0.5871 | | 0.877 | 22.83 | 10500 | 1.2577 | 0.5664 | 0.5668 | | 0.8758 | 23.91 | 11000 | 1.2432 | 0.5818 | 0.5808 | | 0.8731 | 25.0 | 11500 | 1.2480 | 0.5660 | 0.5678 | | 0.8715 | 26.09 | 12000 | 1.2488 | 0.5544 | 0.5550 | | 0.8688 | 27.17 | 12500 | 1.2414 | 0.5768 | 0.5786 | | 0.8667 | 28.26 | 13000 | 1.2339 | 0.5756 | 0.5711 | | 0.8661 | 29.35 | 13500 | 1.2204 | 0.5903 | 0.5911 | | 0.8644 | 30.43 | 14000 | 1.2427 | 0.5656 | 0.5673 | | 0.862 | 31.52 | 14500 | 1.2421 | 0.5799 | 0.5810 | | 0.8611 | 32.61 | 15000 | 1.2375 | 0.5764 | 0.5759 | | 0.8612 | 33.7 | 15500 | 1.2184 | 0.6003 | 0.5975 | | 0.8583 | 34.78 | 16000 | 1.2345 | 0.5841 | 0.5851 | | 0.8585 | 35.87 | 16500 | 1.2324 | 0.5841 | 0.5849 | | 0.8569 | 36.96 | 17000 | 1.2308 | 0.5818 | 0.5817 | | 0.8553 | 38.04 | 17500 | 1.2209 | 0.5968 | 0.5949 | | 0.8547 | 39.13 | 18000 | 1.2301 | 0.5853 | 0.5859 | | 0.8547 | 40.22 | 18500 | 1.2211 | 0.5887 | 0.5874 | | 0.8532 | 41.3 | 19000 | 1.2224 | 0.5895 | 0.5912 | | 0.853 | 42.39 | 19500 | 1.2245 | 0.5829 | 0.5844 | | 0.8523 | 43.48 | 20000 | 1.2187 | 0.5945 | 0.5947 | | 0.8521 | 44.57 | 20500 | 1.2141 | 0.5965 | 0.5959 | | 0.851 | 45.65 | 21000 | 1.2122 | 0.6011 | 0.6016 | | 0.8512 | 46.74 | 21500 | 1.2176 | 0.5941 | 0.5944 | | 0.8507 | 47.83 | 22000 | 1.2161 | 0.5934 | 0.5943 | | 0.8503 | 48.91 | 22500 | 1.2157 | 0.5957 | 0.5966 | | 0.8501 | 50.0 | 23000 | 1.2134 | 0.5976 | 0.5983 | ### Framework versions - Transformers 4.33.3 - Pytorch 2.1.1+cu121 - Datasets 2.14.5 - Tokenizers 0.13.3