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segformer-b3-from-scratch-final

This model is a fine-tuned version of on the samitizerxu/kelp_data_rgbagg_swin_nir_int_cleaned dataset. It achieves the following results on the evaluation set:

  • Iou Kelp: 0.0073
  • Loss: 0.9864

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: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • num_epochs: 60

Training results

Training Loss Epoch Step Iou Kelp Validation Loss
0.9993 0.18 100 0.0069 0.9867
0.9945 0.37 200 0.0076 0.9855
0.9991 0.55 300 0.0069 0.9867
0.999 0.74 400 0.0066 0.9870
0.9959 0.92 500 0.0071 0.9864
0.9965 1.11 600 0.0066 0.9871
0.9764 1.29 700 0.0066 0.9871
0.9951 1.48 800 0.0066 0.9871
0.9999 1.66 900 0.0066 0.9870
0.9878 1.85 1000 0.0066 0.9871
0.9978 2.03 1100 0.0066 0.9871
0.975 2.21 1200 0.0069 0.9868
0.9957 2.4 1300 0.0073 0.9859
0.9914 2.58 1400 0.0079 0.9860
0.9928 2.77 1500 0.0074 0.9859
0.9994 2.95 1600 0.0004 0.9863
0.995 3.14 1700 0.0101 0.9860
0.9963 3.32 1800 0.0 0.9872
0.9972 3.51 1900 0.0074 0.9858
0.9959 3.69 2000 0.0076 0.9859
0.9941 3.87 2100 0.0073 0.9859
0.992 4.06 2200 0.0002 0.9951
0.9903 4.24 2300 0.0073 0.9859
0.9989 4.43 2400 0.0066 0.9871
0.9999 4.61 2500 0.0073 0.9866
0.9946 4.8 2600 0.0073 0.9859
0.9959 4.98 2700 0.0073 0.9859
0.9971 5.17 2800 0.0079 0.9863
0.9949 5.35 2900 0.0074 0.9859
0.9846 5.54 3000 0.0073 0.9859
0.9941 5.72 3100 0.0074 0.9859
0.9867 5.9 3200 0.0074 0.9858
0.9857 6.09 3300 0.0074 0.9861
0.9986 6.27 3400 0.0074 0.9859
0.9927 6.46 3500 0.0074 0.9860
0.998 6.64 3600 0.0075 0.9858
0.9971 6.83 3700 0.0074 0.9859
0.9951 7.01 3800 0.0074 0.9859
0.9998 7.2 3900 0.0074 0.9861
0.995 7.38 4000 0.0075 0.9858
0.9912 7.56 4100 0.0072 0.9861
0.9995 7.75 4200 0.0074 0.9858
0.9934 7.93 4300 0.0074 0.9860
0.9885 8.12 4400 0.0074 0.9860
0.9937 8.3 4500 0.0075 0.9857
0.9954 8.49 4600 0.0075 0.9857
0.9794 8.67 4700 0.0074 0.9858
0.9967 8.86 4800 0.0075 0.9857
0.9954 9.04 4900 0.0074 0.9862
0.9966 9.23 5000 0.0074 0.9859
0.9953 9.41 5100 0.0074 0.9859
0.9961 9.59 5200 0.0074 0.9859
0.993 9.78 5300 0.0075 0.9858
0.9993 9.96 5400 0.0070 0.9870
0.995 10.15 5500 0.0032 0.9933
0.9945 10.33 5600 0.0061 0.9884
0.9738 10.52 5700 0.0069 0.9866
0.9983 10.7 5800 0.0067 0.9869
0.9975 10.89 5900 0.0076 0.9854
0.9925 11.07 6000 0.0086 0.9839
0.9821 11.25 6100 0.0092 0.9822
0.9972 11.44 6200 0.0107 0.9787
0.9802 11.62 6300 0.0109 0.9781
1.0 11.81 6400 0.0076 0.9854
0.9922 11.99 6500 0.0108 0.9793
0.9915 12.18 6600 0.0108 0.9799
0.9963 12.36 6700 0.0075 0.9857
0.9966 12.55 6800 0.0075 0.9859
0.9978 12.73 6900 0.0069 0.9870
0.9847 12.92 7000 0.0074 0.9860
0.9972 13.1 7100 0.0072 0.9862
0.9868 13.28 7200 0.0071 0.9865
0.9961 13.47 7300 0.0072 0.9864
0.9845 13.65 7400 0.0071 0.9865
0.9974 13.84 7500 0.0074 0.9862
0.9906 14.02 7600 0.0076 0.9847
0.9999 14.21 7700 0.0075 0.9860
0.9821 14.39 7800 0.0074 0.9860
0.9976 14.58 7900 0.0105 0.9795
0.9871 14.76 8000 0.0103 0.9803
0.991 14.94 8100 0.0102 0.9805
0.9903 15.13 8200 0.0104 0.9799
0.995 15.31 8300 0.0074 0.9861
0.9981 15.5 8400 0.0073 0.9863
0.9985 15.68 8500 0.0073 0.9863
0.9973 15.87 8600 0.0074 0.9862
0.989 16.05 8700 0.0073 0.9863
0.9938 16.24 8800 0.0074 0.9860
0.9951 16.42 8900 0.0106 0.9786
0.9921 16.61 9000 0.0092 0.9824
0.9971 16.79 9100 0.0083 0.9846
0.9846 16.97 9200 0.0087 0.9838
0.9849 17.16 9300 0.0095 0.9820
0.9851 17.34 9400 0.0096 0.9818
0.9902 17.53 9500 0.0099 0.9811
0.9889 17.71 9600 0.0075 0.9860
0.9782 17.9 9700 0.0075 0.9908
0.999 18.08 9800 0.0074 0.9862
0.9878 18.27 9900 0.0073 0.9862
0.999 18.45 10000 0.0074 0.9862
1.0 18.63 10100 0.0074 0.9861
0.9951 18.82 10200 0.0075 0.9859
0.9892 19.0 10300 0.0073 0.9861
0.9853 19.19 10400 0.0074 0.9859
0.9959 19.37 10500 0.0074 0.9859
0.9999 19.56 10600 0.0073 0.9861
0.9872 19.74 10700 0.0074 0.9859
0.9939 19.93 10800 0.0074 0.9861
0.9924 20.11 10900 0.0073 0.9862
0.9993 20.3 11000 0.0074 0.9860
0.9934 20.48 11100 0.0075 0.9858
0.9976 20.66 11200 0.0074 0.9859
0.9878 20.85 11300 0.0074 0.9859
0.9955 21.03 11400 0.0074 0.9859
0.9878 21.22 11500 0.0075 0.9859
0.999 21.4 11600 0.0074 0.9859
0.9945 21.59 11700 0.0074 0.9861
0.994 21.77 11800 0.0075 0.9859
0.9848 21.96 11900 0.0075 0.9859
0.9998 22.14 12000 0.0075 0.9859
0.9826 22.32 12100 0.0075 0.9859
0.999 22.51 12200 0.0074 0.9861
0.9941 22.69 12300 0.0073 0.9863
0.9933 22.88 12400 0.0074 0.9862
0.9935 23.06 12500 0.0074 0.9862
0.9992 23.25 12600 0.0073 0.9863
0.9943 23.43 12700 0.0073 0.9863
0.9777 23.62 12800 0.0075 0.9858
0.9977 23.8 12900 0.0073 0.9862
0.9925 23.99 13000 0.0074 0.9861
0.9866 24.17 13100 0.0073 0.9863
0.9979 24.35 13200 0.0073 0.9862
0.9819 24.54 13300 0.0073 0.9864
0.966 24.72 13400 0.0073 0.9864
0.998 24.91 13500 0.0073 0.9863
0.9969 25.09 13600 0.0073 0.9863
0.9881 25.28 13700 0.0073 0.9863
0.9701 25.46 13800 0.0073 0.9864
0.9963 25.65 13900 0.0073 0.9863
0.9885 25.83 14000 0.0073 0.9863
0.9904 26.01 14100 0.0073 0.9864
0.9976 26.2 14200 0.0074 0.9862
0.995 26.38 14300 0.0073 0.9863
0.9886 26.57 14400 0.0073 0.9864
0.9735 26.75 14500 0.0073 0.9863
0.988 26.94 14600 0.0073 0.9864
0.9854 27.12 14700 0.0073 0.9864
0.9947 27.31 14800 0.0073 0.9864
0.9944 27.49 14900 0.0073 0.9864
0.9935 27.68 15000 0.0073 0.9862
0.9887 27.86 15100 0.0073 0.9863
0.9958 28.04 15200 0.0073 0.9862
0.9994 28.23 15300 0.0073 0.9863
0.9953 28.41 15400 0.0073 0.9868
0.9798 28.6 15500 0.0073 0.9863
0.9867 28.78 15600 0.0073 0.9863
0.9903 28.97 15700 0.0073 0.9863
0.9943 29.15 15800 0.0073 0.9864
0.9725 29.34 15900 0.0072 0.9864
0.9987 29.52 16000 0.0073 0.9864
0.9871 29.7 16100 0.0072 0.9864
0.992 29.89 16200 0.0072 0.9864
0.996 30.07 16300 0.0073 0.9864
0.9998 30.26 16400 0.0073 0.9864
0.9964 30.44 16500 0.0074 0.9859
0.9992 30.63 16600 0.0075 0.9858
0.9946 30.81 16700 0.0074 0.9861
0.9911 31.0 16800 0.0075 0.9859
0.9878 31.18 16900 0.0075 0.9859
0.9826 31.37 17000 0.0075 0.9859
0.9894 31.55 17100 0.0075 0.9859
0.9887 31.73 17200 0.0075 0.9860
0.9962 31.92 17300 0.0073 0.9862
0.9937 32.1 17400 0.0073 0.9863
0.9828 32.29 17500 0.0073 0.9863
0.993 32.47 17600 0.0073 0.9864
0.9975 32.66 17700 0.0073 0.9864
0.994 32.84 17800 0.0073 0.9864
0.9894 33.03 17900 0.0073 0.9862
0.9938 33.21 18000 0.0073 0.9863
0.9711 33.39 18100 0.0073 0.9863
0.9896 33.58 18200 0.0073 0.9864
0.9907 33.76 18300 0.0073 0.9864
0.9934 33.95 18400 0.0073 0.9864
0.9723 34.13 18500 0.0073 0.9864
0.9842 34.32 18600 0.0073 0.9864
0.9955 34.5 18700 0.0073 0.9864
0.9824 34.69 18800 0.0073 0.9864
0.9949 34.87 18900 0.0073 0.9864
0.9943 35.06 19000 0.0073 0.9864
0.9992 35.24 19100 0.0073 0.9864
0.9843 35.42 19200 0.0073 0.9864
0.9785 35.61 19300 0.0073 0.9864
0.9999 35.79 19400 0.0073 0.9864
0.9727 35.98 19500 0.0073 0.9864
0.9949 36.16 19600 0.0073 0.9864
0.9949 36.35 19700 0.0073 0.9864
0.9887 36.53 19800 0.0073 0.9864
0.9736 36.72 19900 0.0073 0.9864
0.9966 36.9 20000 0.0073 0.9864
0.9984 37.08 20100 0.0073 0.9864
0.993 37.27 20200 0.0073 0.9864
0.9998 37.45 20300 0.0073 0.9864
0.9972 37.64 20400 0.0073 0.9864
0.986 37.82 20500 0.0073 0.9864
0.9914 38.01 20600 0.0073 0.9864
0.9954 38.19 20700 0.0073 0.9864
0.9764 38.38 20800 0.0073 0.9864
0.9953 38.56 20900 0.0073 0.9864
0.9837 38.75 21000 0.0073 0.9864
0.9665 38.93 21100 0.0073 0.9864
0.9964 39.11 21200 0.0073 0.9864
0.9935 39.3 21300 0.0073 0.9864
0.9466 39.48 21400 0.0073 0.9864
0.9853 39.67 21500 0.0073 0.9864
0.9678 39.85 21600 0.0073 0.9864
0.995 40.04 21700 0.0073 0.9864
0.9987 40.22 21800 0.0073 0.9864
0.9935 40.41 21900 0.0073 0.9864
0.991 40.59 22000 0.0073 0.9864
0.999 40.77 22100 0.0073 0.9864
0.9985 40.96 22200 0.0073 0.9864
0.9954 41.14 22300 0.0073 0.9864
0.9894 41.33 22400 0.0073 0.9864
0.9851 41.51 22500 0.0073 0.9864
0.9882 41.7 22600 0.0073 0.9864
0.9999 41.88 22700 0.0073 0.9864
0.9901 42.07 22800 0.0073 0.9864
0.9853 42.25 22900 0.0073 0.9864
0.9868 42.44 23000 0.0073 0.9864
0.9973 42.62 23100 0.0073 0.9864
0.9979 42.8 23200 0.0073 0.9865
0.9867 42.99 23300 0.0073 0.9864
0.9994 43.17 23400 0.0073 0.9864
0.9984 43.36 23500 0.0073 0.9865
0.9974 43.54 23600 0.0073 0.9865
0.9999 43.73 23700 0.0073 0.9864
0.9669 43.91 23800 0.0073 0.9864
0.9925 44.1 23900 0.0073 0.9864
0.9961 44.28 24000 0.0073 0.9864
0.9815 44.46 24100 0.0073 0.9864
0.9968 44.65 24200 0.0073 0.9864
0.9964 44.83 24300 0.0073 0.9864
0.9929 45.02 24400 0.0073 0.9864
0.9712 45.2 24500 0.0073 0.9864
0.9884 45.39 24600 0.0073 0.9864
0.9897 45.57 24700 0.0073 0.9864
0.9862 45.76 24800 0.0073 0.9865
0.9768 45.94 24900 0.0073 0.9865
0.9965 46.13 25000 0.0073 0.9865
0.9996 46.31 25100 0.0073 0.9864
0.9887 46.49 25200 0.0073 0.9864
0.9991 46.68 25300 0.0073 0.9864
0.984 46.86 25400 0.0073 0.9864
0.983 47.05 25500 0.0073 0.9864
0.9997 47.23 25600 0.0073 0.9864
0.9923 47.42 25700 0.0073 0.9865
0.9962 47.6 25800 0.0073 0.9864
0.9747 47.79 25900 0.0073 0.9864
0.9981 47.97 26000 0.0073 0.9864
0.9936 48.15 26100 0.0073 0.9864
0.9976 48.34 26200 0.0073 0.9864
0.9601 48.52 26300 0.0073 0.9865
0.9881 48.71 26400 0.0073 0.9864
0.9919 48.89 26500 0.0073 0.9864
0.9748 49.08 26600 0.0073 0.9864
0.9862 49.26 26700 0.0073 0.9864
0.9935 49.45 26800 0.0073 0.9864
0.9402 49.63 26900 0.0073 0.9864
0.9982 49.82 27000 0.0073 0.9864
0.9619 50.0 27100 0.0073 0.9864
0.9935 50.18 27200 0.0073 0.9864
0.9962 50.37 27300 0.0073 0.9864
0.9888 50.55 27400 0.0073 0.9864
0.9956 50.74 27500 0.0073 0.9864
0.9981 50.92 27600 0.0073 0.9864
0.9992 51.11 27700 0.0073 0.9865
0.9613 51.29 27800 0.0073 0.9864
0.9721 51.48 27900 0.0072 0.9865
0.9938 51.66 28000 0.0073 0.9865
0.9998 51.85 28100 0.0073 0.9864
0.9981 52.03 28200 0.0073 0.9864
0.9793 52.21 28300 0.0073 0.9864
0.9962 52.4 28400 0.0073 0.9864
0.9728 52.58 28500 0.0073 0.9864
0.9965 52.77 28600 0.0073 0.9864
0.9937 52.95 28700 0.0073 0.9864
0.9942 53.14 28800 0.0073 0.9864
0.9902 53.32 28900 0.0073 0.9864
0.9992 53.51 29000 0.0073 0.9864
0.9954 53.69 29100 0.0073 0.9864
0.991 53.87 29200 0.0073 0.9864
0.9955 54.06 29300 0.0073 0.9864
0.9978 54.24 29400 0.0073 0.9864
0.9998 54.43 29500 0.0073 0.9864
0.9716 54.61 29600 0.0073 0.9864
0.9891 54.8 29700 0.0073 0.9864
0.9984 54.98 29800 0.0073 0.9864
0.9756 55.17 29900 0.0073 0.9864
0.9901 55.35 30000 0.0073 0.9864
0.9866 55.54 30100 0.0073 0.9864
0.9908 55.72 30200 0.0073 0.9864
0.977 55.9 30300 0.0073 0.9864
0.9882 56.09 30400 0.0073 0.9864
0.9903 56.27 30500 0.0073 0.9864
0.9819 56.46 30600 0.0073 0.9864
0.9883 56.64 30700 0.0073 0.9864
0.9922 56.83 30800 0.0073 0.9864
0.9788 57.01 30900 0.0073 0.9864
0.9756 57.2 31000 0.0073 0.9864
0.9955 57.38 31100 0.0073 0.9864
0.9925 57.56 31200 0.0073 0.9864
0.9976 57.75 31300 0.0073 0.9864
0.9938 57.93 31400 0.0073 0.9864
0.9905 58.12 31500 0.0073 0.9864
0.9819 58.3 31600 0.0073 0.9864
0.9827 58.49 31700 0.0073 0.9864
0.9927 58.67 31800 0.0073 0.9864
0.9953 58.86 31900 0.0073 0.9864
0.9937 59.04 32000 0.0073 0.9864
0.9961 59.23 32100 0.0073 0.9864
0.9886 59.41 32200 0.0073 0.9864
0.9906 59.59 32300 0.0073 0.9864
0.9811 59.78 32400 0.0073 0.9864
0.9977 59.96 32500 0.0073 0.9864

Framework versions

  • Transformers 4.37.2
  • Pytorch 2.2.0
  • Datasets 2.17.0
  • Tokenizers 0.15.1
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