--- library_name: transformers base_model: Rostlab/prot_t5_xl_uniref50 tags: - generated_from_trainer model-index: - name: msa_prot_t5 results: [] --- # msa_prot_t5 This model is a fine-tuned version of [Rostlab/prot_t5_xl_uniref50](https://huggingface.co/Rostlab/prot_t5_xl_uniref50) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 2.8955 ## 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: 0.001 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - num_epochs: 100 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-----:|:-----:|:---------------:| | 2.9094 | 1.0 | 356 | 2.9027 | | 2.8947 | 2.0 | 712 | 2.8965 | | 2.901 | 3.0 | 1068 | 2.8935 | | 2.9007 | 4.0 | 1424 | 2.8933 | | 2.9028 | 5.0 | 1780 | 2.9093 | | 2.8926 | 6.0 | 2136 | 2.9062 | | 2.9033 | 7.0 | 2492 | 2.8993 | | 2.9039 | 8.0 | 2848 | 2.9036 | | 2.8954 | 9.0 | 3204 | 2.8962 | | 2.9046 | 10.0 | 3560 | 2.9003 | | 2.9031 | 11.0 | 3916 | 2.9030 | | 2.9066 | 12.0 | 4272 | 2.9033 | | 2.893 | 13.0 | 4628 | 2.9013 | | 2.8927 | 14.0 | 4984 | 2.8975 | | 2.9021 | 15.0 | 5340 | 2.8938 | | 2.898 | 16.0 | 5696 | 2.8850 | | 2.9036 | 17.0 | 6052 | 2.8970 | | 2.9078 | 18.0 | 6408 | 2.8901 | | 2.9101 | 19.0 | 6764 | 2.8927 | | 2.892 | 20.0 | 7120 | 2.8840 | | 2.9044 | 21.0 | 7476 | 2.8920 | | 2.8989 | 22.0 | 7832 | 2.8835 | | 2.8949 | 23.0 | 8188 | 2.8939 | | 2.8987 | 24.0 | 8544 | 2.8961 | | 2.9021 | 25.0 | 8900 | 2.8932 | | 2.8935 | 26.0 | 9256 | 2.8856 | | 2.8949 | 27.0 | 9612 | 2.8968 | | 2.8974 | 28.0 | 9968 | 2.8888 | | 2.8922 | 29.0 | 10324 | 2.9046 | | 2.9028 | 30.0 | 10680 | 2.8931 | | 2.8978 | 31.0 | 11036 | 2.8963 | | 2.8977 | 32.0 | 11392 | 2.8920 | | 2.9044 | 33.0 | 11748 | 2.9045 | | 2.8966 | 34.0 | 12104 | 2.8918 | | 2.898 | 35.0 | 12460 | 2.8981 | | 2.9051 | 36.0 | 12816 | 2.8973 | | 2.9046 | 37.0 | 13172 | 2.8868 | | 2.9011 | 38.0 | 13528 | 2.9006 | | 2.8903 | 39.0 | 13884 | 2.8997 | | 2.907 | 40.0 | 14240 | 2.8961 | | 2.9088 | 41.0 | 14596 | 2.8939 | | 2.8976 | 42.0 | 14952 | 2.8994 | | 2.9023 | 43.0 | 15308 | 2.8867 | | 2.8879 | 44.0 | 15664 | 2.8917 | | 2.89 | 45.0 | 16020 | 2.8878 | | 2.889 | 46.0 | 16376 | 2.8945 | | 2.8947 | 47.0 | 16732 | 2.8930 | | 2.8911 | 48.0 | 17088 | 2.9011 | | 2.8939 | 49.0 | 17444 | 2.8833 | | 2.897 | 50.0 | 17800 | 2.8949 | | 2.8925 | 51.0 | 18156 | 2.8942 | | 2.8928 | 52.0 | 18512 | 2.8832 | | 2.9042 | 53.0 | 18868 | 2.8860 | | 2.8944 | 54.0 | 19224 | 2.8948 | | 2.9032 | 55.0 | 19580 | 2.8948 | | 2.9003 | 56.0 | 19936 | 2.8877 | | 2.9017 | 57.0 | 20292 | 2.9022 | | 2.8963 | 58.0 | 20648 | 2.8900 | | 2.9042 | 59.0 | 21004 | 2.9029 | | 2.8911 | 60.0 | 21360 | 2.8832 | | 2.9007 | 61.0 | 21716 | 2.8943 | | 2.8952 | 62.0 | 22072 | 2.8984 | | 2.9003 | 63.0 | 22428 | 2.8929 | | 2.8932 | 64.0 | 22784 | 2.8967 | | 2.9033 | 65.0 | 23140 | 2.9023 | | 2.8993 | 66.0 | 23496 | 2.8929 | | 2.8999 | 67.0 | 23852 | 2.8924 | | 2.8857 | 68.0 | 24208 | 2.8979 | | 2.8924 | 69.0 | 24564 | 2.8934 | | 2.9083 | 70.0 | 24920 | 2.8890 | | 2.901 | 71.0 | 25276 | 2.9047 | | 2.9026 | 72.0 | 25632 | 2.8877 | | 2.8991 | 73.0 | 25988 | 2.8871 | | 2.8983 | 74.0 | 26344 | 2.8865 | | 2.8895 | 75.0 | 26700 | 2.9036 | | 2.8957 | 76.0 | 27056 | 2.8920 | | 2.8963 | 77.0 | 27412 | 2.8911 | | 2.9062 | 78.0 | 27768 | 2.9045 | | 2.8931 | 79.0 | 28124 | 2.8963 | | 2.9065 | 80.0 | 28480 | 2.8876 | | 2.892 | 81.0 | 28836 | 2.8762 | | 2.8985 | 82.0 | 29192 | 2.8965 | | 2.8969 | 83.0 | 29548 | 2.8994 | | 2.8885 | 84.0 | 29904 | 2.9030 | | 2.9047 | 85.0 | 30260 | 2.8905 | | 2.8987 | 86.0 | 30616 | 2.8993 | | 2.9029 | 87.0 | 30972 | 2.8878 | | 2.8994 | 88.0 | 31328 | 2.8911 | | 2.8884 | 89.0 | 31684 | 2.8911 | | 2.8954 | 90.0 | 32040 | 2.8959 | | 2.8952 | 91.0 | 32396 | 2.8860 | | 2.896 | 92.0 | 32752 | 2.8820 | | 2.9001 | 93.0 | 33108 | 2.8878 | | 2.902 | 94.0 | 33464 | 2.8862 | | 2.8946 | 95.0 | 33820 | 2.8943 | | 2.892 | 96.0 | 34176 | 2.8932 | | 2.8918 | 97.0 | 34532 | 2.8967 | | 2.9073 | 98.0 | 34888 | 2.8972 | | 2.903 | 99.0 | 35244 | 2.8981 | | 2.8984 | 100.0 | 35600 | 2.8955 | ### Framework versions - Transformers 4.51.3 - Pytorch 2.7.0+cu126 - Datasets 3.5.0 - Tokenizers 0.21.1