--- license: mit base_model: FacebookAI/xlm-roberta-base tags: - generated_from_trainer metrics: - accuracy - f1 model-index: - name: XMLRoberta_Lexical_Dataset59KBoDuoi results: [] --- # XMLRoberta_Lexical_Dataset59KBoDuoi This model is a fine-tuned version of [FacebookAI/xlm-roberta-base](https://huggingface.co/FacebookAI/xlm-roberta-base) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.6232 - Accuracy: 0.8988 - F1: 0.8992 ## 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: 2e-05 - train_batch_size: 64 - eval_batch_size: 64 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 20 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |:-------------:|:-------:|:-----:|:---------------:|:--------:|:------:| | No log | 0.2558 | 200 | 0.4593 | 0.7916 | 0.7880 | | No log | 0.5115 | 400 | 0.3779 | 0.8222 | 0.8249 | | No log | 0.7673 | 600 | 0.3462 | 0.8514 | 0.8497 | | 0.4345 | 1.0230 | 800 | 0.3543 | 0.8554 | 0.8513 | | 0.4345 | 1.2788 | 1000 | 0.3504 | 0.8573 | 0.8537 | | 0.4345 | 1.5345 | 1200 | 0.3033 | 0.8767 | 0.8772 | | 0.4345 | 1.7903 | 1400 | 0.2834 | 0.8778 | 0.8788 | | 0.3071 | 2.0460 | 1600 | 0.3207 | 0.8671 | 0.8695 | | 0.3071 | 2.3018 | 1800 | 0.2959 | 0.8822 | 0.8814 | | 0.3071 | 2.5575 | 2000 | 0.2821 | 0.8778 | 0.8781 | | 0.3071 | 2.8133 | 2200 | 0.3024 | 0.8872 | 0.8883 | | 0.2523 | 3.0691 | 2400 | 0.2972 | 0.8888 | 0.8894 | | 0.2523 | 3.3248 | 2600 | 0.2746 | 0.8883 | 0.8891 | | 0.2523 | 3.5806 | 2800 | 0.2828 | 0.8909 | 0.8911 | | 0.2523 | 3.8363 | 3000 | 0.2822 | 0.8941 | 0.8941 | | 0.2177 | 4.0921 | 3200 | 0.2995 | 0.8898 | 0.8910 | | 0.2177 | 4.3478 | 3400 | 0.2953 | 0.8887 | 0.8898 | | 0.2177 | 4.6036 | 3600 | 0.2944 | 0.8925 | 0.8931 | | 0.2177 | 4.8593 | 3800 | 0.3006 | 0.8957 | 0.8958 | | 0.189 | 5.1151 | 4000 | 0.2816 | 0.8950 | 0.8955 | | 0.189 | 5.3708 | 4200 | 0.2865 | 0.8956 | 0.8960 | | 0.189 | 5.6266 | 4400 | 0.2794 | 0.8961 | 0.8966 | | 0.189 | 5.8824 | 4600 | 0.2836 | 0.8980 | 0.8986 | | 0.1637 | 6.1381 | 4800 | 0.3399 | 0.8949 | 0.8951 | | 0.1637 | 6.3939 | 5000 | 0.3248 | 0.8952 | 0.8957 | | 0.1637 | 6.6496 | 5200 | 0.3341 | 0.8976 | 0.8979 | | 0.1637 | 6.9054 | 5400 | 0.2993 | 0.8962 | 0.8970 | | 0.1388 | 7.1611 | 5600 | 0.3662 | 0.8967 | 0.8978 | | 0.1388 | 7.4169 | 5800 | 0.3761 | 0.8962 | 0.8968 | | 0.1388 | 7.6726 | 6000 | 0.3305 | 0.8953 | 0.8961 | | 0.1388 | 7.9284 | 6200 | 0.3328 | 0.8966 | 0.8970 | | 0.1193 | 8.1841 | 6400 | 0.3753 | 0.8980 | 0.8985 | | 0.1193 | 8.4399 | 6600 | 0.3646 | 0.8974 | 0.8976 | | 0.1193 | 8.6957 | 6800 | 0.3800 | 0.8963 | 0.8966 | | 0.1193 | 8.9514 | 7000 | 0.3472 | 0.8980 | 0.8987 | | 0.1059 | 9.2072 | 7200 | 0.3991 | 0.9002 | 0.9004 | | 0.1059 | 9.4629 | 7400 | 0.4026 | 0.8967 | 0.8978 | | 0.1059 | 9.7187 | 7600 | 0.3915 | 0.8983 | 0.8983 | | 0.1059 | 9.9744 | 7800 | 0.3932 | 0.8997 | 0.8999 | | 0.0923 | 10.2302 | 8000 | 0.4887 | 0.8939 | 0.8947 | | 0.0923 | 10.4859 | 8200 | 0.4074 | 0.8977 | 0.8981 | | 0.0923 | 10.7417 | 8400 | 0.3931 | 0.8998 | 0.9003 | | 0.0806 | 10.9974 | 8600 | 0.4131 | 0.8955 | 0.8964 | | 0.0806 | 11.2532 | 8800 | 0.4499 | 0.8963 | 0.8970 | | 0.0806 | 11.5090 | 9000 | 0.4436 | 0.8999 | 0.9002 | | 0.0806 | 11.7647 | 9200 | 0.4842 | 0.8965 | 0.8968 | | 0.0697 | 12.0205 | 9400 | 0.4851 | 0.8961 | 0.8963 | | 0.0697 | 12.2762 | 9600 | 0.5138 | 0.8999 | 0.9002 | | 0.0697 | 12.5320 | 9800 | 0.5020 | 0.8963 | 0.8964 | | 0.0697 | 12.7877 | 10000 | 0.5108 | 0.8929 | 0.8940 | | 0.064 | 13.0435 | 10200 | 0.4893 | 0.8966 | 0.8968 | | 0.064 | 13.2992 | 10400 | 0.5052 | 0.8973 | 0.8980 | | 0.064 | 13.5550 | 10600 | 0.4917 | 0.8970 | 0.8971 | | 0.064 | 13.8107 | 10800 | 0.5087 | 0.8965 | 0.8968 | | 0.0571 | 14.0665 | 11000 | 0.5195 | 0.8970 | 0.8977 | | 0.0571 | 14.3223 | 11200 | 0.5279 | 0.8932 | 0.8943 | | 0.0571 | 14.5780 | 11400 | 0.5015 | 0.8974 | 0.8978 | | 0.0571 | 14.8338 | 11600 | 0.5301 | 0.8961 | 0.8965 | | 0.0538 | 15.0895 | 11800 | 0.5297 | 0.8951 | 0.8952 | | 0.0538 | 15.3453 | 12000 | 0.5573 | 0.8976 | 0.8980 | | 0.0538 | 15.6010 | 12200 | 0.5579 | 0.8955 | 0.8962 | | 0.0538 | 15.8568 | 12400 | 0.5814 | 0.8969 | 0.8968 | | 0.0481 | 16.1125 | 12600 | 0.5861 | 0.8972 | 0.8974 | | 0.0481 | 16.3683 | 12800 | 0.5871 | 0.8968 | 0.8972 | | 0.0481 | 16.6240 | 13000 | 0.5913 | 0.8978 | 0.8986 | | 0.0481 | 16.8798 | 13200 | 0.6100 | 0.8957 | 0.8967 | | 0.043 | 17.1355 | 13400 | 0.5895 | 0.8976 | 0.8982 | | 0.043 | 17.3913 | 13600 | 0.5653 | 0.8978 | 0.8982 | | 0.043 | 17.6471 | 13800 | 0.5914 | 0.8996 | 0.8999 | | 0.043 | 17.9028 | 14000 | 0.5850 | 0.9005 | 0.9007 | | 0.042 | 18.1586 | 14200 | 0.5927 | 0.8983 | 0.8988 | | 0.042 | 18.4143 | 14400 | 0.6164 | 0.8997 | 0.8999 | | 0.042 | 18.6701 | 14600 | 0.6324 | 0.8986 | 0.8992 | | 0.042 | 18.9258 | 14800 | 0.6097 | 0.8996 | 0.9001 | | 0.0383 | 19.1816 | 15000 | 0.6029 | 0.8985 | 0.8989 | | 0.0383 | 19.4373 | 15200 | 0.6067 | 0.8988 | 0.8992 | | 0.0383 | 19.6931 | 15400 | 0.6177 | 0.8987 | 0.8991 | | 0.0383 | 19.9488 | 15600 | 0.6232 | 0.8988 | 0.8992 | ### Framework versions - Transformers 4.41.2 - Pytorch 2.1.2 - Datasets 2.19.2 - Tokenizers 0.19.1