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segformer-b5-p142-cvat-vgs

Image Segmentation
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  1. README.md +239 -0
  2. config.json +78 -0
  3. model.safetensors +3 -0
  4. runs/Apr26_02-20-57_Vigneshs-MacBook-Pro.local/events.out.tfevents.1714078560.Vigneshs-MacBook-Pro.local.30689.0 +3 -0
  5. training_args.bin +3 -0
README.md ADDED
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+ ---
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+ license: other
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+ base_model: nvidia/mit-b5
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+ tags:
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+ - vision
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+ - image-segmentation
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+ - generated_from_trainer
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+ model-index:
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+ - name: segformer-b5-p142-cvat-vgs
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # segformer-b5-p142-cvat-vgs
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+
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+ This model is a fine-tuned version of [nvidia/mit-b5](https://huggingface.co/nvidia/mit-b5) on the vigneshgs7/segformer_open_cv_RGB_L_0_1 dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0131
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+ - Mean Iou: 0.4961
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+ - Mean Accuracy: 0.9922
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+ - Overall Accuracy: 0.9922
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+ - Accuracy Background: nan
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+ - Accuracy Object: 0.9922
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+ - Iou Background: 0.0
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+ - Iou Object: 0.9922
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 1e-05
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+ - train_batch_size: 2
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+ - eval_batch_size: 2
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+ - seed: 42
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - num_epochs: 10
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Background | Accuracy Object | Iou Background | Iou Object |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:-------------------:|:---------------:|:--------------:|:----------:|
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+ | 0.2847 | 0.06 | 20 | 0.3843 | 0.4662 | 0.9324 | 0.9324 | nan | 0.9324 | 0.0 | 0.9324 |
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+ | 0.1681 | 0.11 | 40 | 0.1983 | 0.4704 | 0.9408 | 0.9408 | nan | 0.9408 | 0.0 | 0.9408 |
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+ | 0.1592 | 0.17 | 60 | 0.1303 | 0.4745 | 0.9489 | 0.9489 | nan | 0.9489 | 0.0 | 0.9489 |
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+ | 0.1177 | 0.23 | 80 | 0.0922 | 0.4944 | 0.9888 | 0.9888 | nan | 0.9888 | 0.0 | 0.9888 |
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+ | 0.062 | 0.29 | 100 | 0.0745 | 0.4946 | 0.9892 | 0.9892 | nan | 0.9892 | 0.0 | 0.9892 |
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+ | 0.0767 | 0.34 | 120 | 0.0545 | 0.4852 | 0.9703 | 0.9703 | nan | 0.9703 | 0.0 | 0.9703 |
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+ | 0.0984 | 0.4 | 140 | 0.0621 | 0.4938 | 0.9875 | 0.9875 | nan | 0.9875 | 0.0 | 0.9875 |
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+ | 0.1779 | 0.46 | 160 | 0.0504 | 0.4961 | 0.9921 | 0.9921 | nan | 0.9921 | 0.0 | 0.9921 |
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+ | 0.0468 | 0.52 | 180 | 0.0407 | 0.4904 | 0.9807 | 0.9807 | nan | 0.9807 | 0.0 | 0.9807 |
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+ | 0.0618 | 0.57 | 200 | 0.0390 | 0.4936 | 0.9873 | 0.9873 | nan | 0.9873 | 0.0 | 0.9873 |
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+ | 0.062 | 0.63 | 220 | 0.0348 | 0.4947 | 0.9894 | 0.9894 | nan | 0.9894 | 0.0 | 0.9894 |
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+ | 0.0357 | 0.69 | 240 | 0.0341 | 0.4914 | 0.9828 | 0.9828 | nan | 0.9828 | 0.0 | 0.9828 |
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+ | 0.0304 | 0.74 | 260 | 0.0351 | 0.4960 | 0.9920 | 0.9920 | nan | 0.9920 | 0.0 | 0.9920 |
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+ | 0.0267 | 0.8 | 280 | 0.0311 | 0.4938 | 0.9877 | 0.9877 | nan | 0.9877 | 0.0 | 0.9877 |
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+ | 0.0536 | 0.86 | 300 | 0.0282 | 0.4904 | 0.9807 | 0.9807 | nan | 0.9807 | 0.0 | 0.9807 |
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+ | 0.049 | 0.92 | 320 | 0.0274 | 0.4928 | 0.9855 | 0.9855 | nan | 0.9855 | 0.0 | 0.9855 |
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+ | 0.0304 | 0.97 | 340 | 0.0262 | 0.4936 | 0.9872 | 0.9872 | nan | 0.9872 | 0.0 | 0.9872 |
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+ | 0.0232 | 1.03 | 360 | 0.0251 | 0.4923 | 0.9847 | 0.9847 | nan | 0.9847 | 0.0 | 0.9847 |
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+ | 0.0304 | 1.09 | 380 | 0.0240 | 0.4917 | 0.9835 | 0.9835 | nan | 0.9835 | 0.0 | 0.9835 |
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+ | 0.0451 | 1.15 | 400 | 0.0261 | 0.4964 | 0.9927 | 0.9927 | nan | 0.9927 | 0.0 | 0.9927 |
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+ | 0.0254 | 1.2 | 420 | 0.0234 | 0.4929 | 0.9859 | 0.9859 | nan | 0.9859 | 0.0 | 0.9859 |
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+ | 0.0354 | 1.26 | 440 | 0.0229 | 0.4931 | 0.9861 | 0.9861 | nan | 0.9861 | 0.0 | 0.9861 |
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+ | 0.2103 | 1.32 | 460 | 0.0224 | 0.4951 | 0.9902 | 0.9902 | nan | 0.9902 | 0.0 | 0.9902 |
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+ | 0.041 | 1.38 | 480 | 0.0222 | 0.4920 | 0.9839 | 0.9839 | nan | 0.9839 | 0.0 | 0.9839 |
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+ | 0.0297 | 1.43 | 500 | 0.0223 | 0.4950 | 0.9900 | 0.9900 | nan | 0.9900 | 0.0 | 0.9900 |
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+ | 0.0299 | 1.49 | 520 | 0.0227 | 0.4961 | 0.9923 | 0.9923 | nan | 0.9923 | 0.0 | 0.9923 |
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+ | 0.0213 | 1.55 | 540 | 0.0209 | 0.4947 | 0.9895 | 0.9895 | nan | 0.9895 | 0.0 | 0.9895 |
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+ | 0.0269 | 1.6 | 560 | 0.0214 | 0.4909 | 0.9817 | 0.9817 | nan | 0.9817 | 0.0 | 0.9817 |
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+ | 0.2199 | 1.66 | 580 | 0.0216 | 0.4956 | 0.9912 | 0.9912 | nan | 0.9912 | 0.0 | 0.9912 |
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+ | 0.0191 | 1.72 | 600 | 0.0208 | 0.4935 | 0.9869 | 0.9869 | nan | 0.9869 | 0.0 | 0.9869 |
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+ | 0.0265 | 1.78 | 620 | 0.0201 | 0.4941 | 0.9882 | 0.9882 | nan | 0.9882 | 0.0 | 0.9882 |
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+ | 0.0244 | 1.83 | 640 | 0.0213 | 0.4910 | 0.9820 | 0.9820 | nan | 0.9820 | 0.0 | 0.9820 |
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+ | 0.0172 | 1.89 | 660 | 0.0199 | 0.4929 | 0.9858 | 0.9858 | nan | 0.9858 | 0.0 | 0.9858 |
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+ | 0.0339 | 1.95 | 680 | 0.0190 | 0.4930 | 0.9859 | 0.9859 | nan | 0.9859 | 0.0 | 0.9859 |
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+ | 0.027 | 2.01 | 700 | 0.0192 | 0.4953 | 0.9906 | 0.9906 | nan | 0.9906 | 0.0 | 0.9906 |
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+ | 0.0221 | 2.06 | 720 | 0.0195 | 0.4915 | 0.9830 | 0.9830 | nan | 0.9830 | 0.0 | 0.9830 |
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+ | 0.0461 | 2.12 | 740 | 0.0188 | 0.4953 | 0.9905 | 0.9905 | nan | 0.9905 | 0.0 | 0.9905 |
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+ | 0.0444 | 2.18 | 760 | 0.0189 | 0.4957 | 0.9914 | 0.9914 | nan | 0.9914 | 0.0 | 0.9914 |
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+ | 0.0211 | 2.23 | 780 | 0.0184 | 0.4949 | 0.9898 | 0.9898 | nan | 0.9898 | 0.0 | 0.9898 |
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+ | 0.0221 | 2.29 | 800 | 0.0186 | 0.4963 | 0.9925 | 0.9925 | nan | 0.9925 | 0.0 | 0.9925 |
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+ | 0.0165 | 2.35 | 820 | 0.0181 | 0.4942 | 0.9883 | 0.9883 | nan | 0.9883 | 0.0 | 0.9883 |
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+ | 0.0171 | 2.41 | 840 | 0.0181 | 0.4923 | 0.9846 | 0.9846 | nan | 0.9846 | 0.0 | 0.9846 |
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+ | 0.0202 | 2.46 | 860 | 0.0178 | 0.4958 | 0.9915 | 0.9915 | nan | 0.9915 | 0.0 | 0.9915 |
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+ | 0.0222 | 2.52 | 880 | 0.0178 | 0.4922 | 0.9844 | 0.9844 | nan | 0.9844 | 0.0 | 0.9844 |
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+ | 0.018 | 2.58 | 900 | 0.0162 | 0.4949 | 0.9898 | 0.9898 | nan | 0.9898 | 0.0 | 0.9898 |
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+ | 0.0288 | 2.64 | 920 | 0.0168 | 0.4943 | 0.9887 | 0.9887 | nan | 0.9887 | 0.0 | 0.9887 |
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+ | 0.016 | 2.69 | 940 | 0.0178 | 0.4968 | 0.9936 | 0.9936 | nan | 0.9936 | 0.0 | 0.9936 |
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+ | 0.0184 | 2.75 | 960 | 0.0172 | 0.4935 | 0.9870 | 0.9870 | nan | 0.9870 | 0.0 | 0.9870 |
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+ | 0.0172 | 2.81 | 980 | 0.0175 | 0.4950 | 0.9900 | 0.9900 | nan | 0.9900 | 0.0 | 0.9900 |
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+ | 0.0168 | 2.87 | 1000 | 0.0172 | 0.4951 | 0.9902 | 0.9902 | nan | 0.9902 | 0.0 | 0.9902 |
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+ | 0.0197 | 2.92 | 1020 | 0.0169 | 0.4961 | 0.9923 | 0.9923 | nan | 0.9923 | 0.0 | 0.9923 |
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+ | 0.0177 | 2.98 | 1040 | 0.0170 | 0.4961 | 0.9922 | 0.9922 | nan | 0.9922 | 0.0 | 0.9922 |
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+ | 0.0377 | 3.04 | 1060 | 0.0163 | 0.4944 | 0.9888 | 0.9888 | nan | 0.9888 | 0.0 | 0.9888 |
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+ | 0.0168 | 3.09 | 1080 | 0.0162 | 0.4953 | 0.9906 | 0.9906 | nan | 0.9906 | 0.0 | 0.9906 |
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+ | 0.0167 | 3.15 | 1100 | 0.0166 | 0.4961 | 0.9922 | 0.9922 | nan | 0.9922 | 0.0 | 0.9922 |
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+ | 0.0213 | 3.21 | 1120 | 0.0164 | 0.4948 | 0.9895 | 0.9895 | nan | 0.9895 | 0.0 | 0.9895 |
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+ | 0.0195 | 3.27 | 1140 | 0.0162 | 0.4947 | 0.9894 | 0.9894 | nan | 0.9894 | 0.0 | 0.9894 |
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+ | 0.014 | 3.32 | 1160 | 0.0160 | 0.4950 | 0.9900 | 0.9900 | nan | 0.9900 | 0.0 | 0.9900 |
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+ | 0.0221 | 3.38 | 1180 | 0.0164 | 0.4961 | 0.9922 | 0.9922 | nan | 0.9922 | 0.0 | 0.9922 |
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+ | 0.0162 | 3.44 | 1200 | 0.0159 | 0.4945 | 0.9890 | 0.9890 | nan | 0.9890 | 0.0 | 0.9890 |
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+ | 0.0153 | 3.5 | 1220 | 0.0152 | 0.4957 | 0.9914 | 0.9914 | nan | 0.9914 | 0.0 | 0.9914 |
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+ | 0.0145 | 3.55 | 1240 | 0.0161 | 0.4935 | 0.9871 | 0.9871 | nan | 0.9871 | 0.0 | 0.9871 |
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+ | 0.0139 | 3.61 | 1260 | 0.0155 | 0.4951 | 0.9902 | 0.9902 | nan | 0.9902 | 0.0 | 0.9902 |
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+ | 0.0153 | 3.67 | 1280 | 0.0157 | 0.4942 | 0.9884 | 0.9884 | nan | 0.9884 | 0.0 | 0.9884 |
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+ | 0.0156 | 3.72 | 1300 | 0.0157 | 0.4949 | 0.9898 | 0.9898 | nan | 0.9898 | 0.0 | 0.9898 |
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+ | 0.033 | 3.78 | 1320 | 0.0157 | 0.4952 | 0.9903 | 0.9903 | nan | 0.9903 | 0.0 | 0.9903 |
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+ | 0.0219 | 3.84 | 1340 | 0.0153 | 0.4957 | 0.9915 | 0.9915 | nan | 0.9915 | 0.0 | 0.9915 |
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+ | 0.0166 | 3.9 | 1360 | 0.0162 | 0.4935 | 0.9871 | 0.9871 | nan | 0.9871 | 0.0 | 0.9871 |
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+ | 0.0168 | 3.95 | 1380 | 0.0157 | 0.4949 | 0.9897 | 0.9897 | nan | 0.9897 | 0.0 | 0.9897 |
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+ | 0.0177 | 4.01 | 1400 | 0.0153 | 0.4966 | 0.9932 | 0.9932 | nan | 0.9932 | 0.0 | 0.9932 |
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+ | 0.0136 | 4.07 | 1420 | 0.0150 | 0.4952 | 0.9905 | 0.9905 | nan | 0.9905 | 0.0 | 0.9905 |
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+ | 0.0334 | 4.13 | 1440 | 0.0156 | 0.4956 | 0.9912 | 0.9912 | nan | 0.9912 | 0.0 | 0.9912 |
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+ | 0.019 | 4.18 | 1460 | 0.0154 | 0.4950 | 0.9899 | 0.9899 | nan | 0.9899 | 0.0 | 0.9899 |
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+ | 0.0147 | 4.24 | 1480 | 0.0148 | 0.4960 | 0.9920 | 0.9920 | nan | 0.9920 | 0.0 | 0.9920 |
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+ | 0.0135 | 4.3 | 1500 | 0.0146 | 0.4951 | 0.9902 | 0.9902 | nan | 0.9902 | 0.0 | 0.9902 |
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+ | 0.0186 | 4.36 | 1520 | 0.0143 | 0.4966 | 0.9933 | 0.9933 | nan | 0.9933 | 0.0 | 0.9933 |
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+ | 0.0153 | 4.41 | 1540 | 0.0141 | 0.4954 | 0.9909 | 0.9909 | nan | 0.9909 | 0.0 | 0.9909 |
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+ | 0.0181 | 4.47 | 1560 | 0.0145 | 0.4954 | 0.9908 | 0.9908 | nan | 0.9908 | 0.0 | 0.9908 |
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+ | 0.0266 | 4.53 | 1580 | 0.0146 | 0.4953 | 0.9907 | 0.9907 | nan | 0.9907 | 0.0 | 0.9907 |
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+ | 0.0141 | 4.58 | 1600 | 0.0147 | 0.4952 | 0.9904 | 0.9904 | nan | 0.9904 | 0.0 | 0.9904 |
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+ | 0.0145 | 4.64 | 1620 | 0.0150 | 0.4947 | 0.9894 | 0.9894 | nan | 0.9894 | 0.0 | 0.9894 |
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+ | 0.0128 | 4.7 | 1640 | 0.0151 | 0.4964 | 0.9928 | 0.9928 | nan | 0.9928 | 0.0 | 0.9928 |
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+ | 0.0119 | 4.76 | 1660 | 0.0143 | 0.4948 | 0.9897 | 0.9897 | nan | 0.9897 | 0.0 | 0.9897 |
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+ | 0.0133 | 4.81 | 1680 | 0.0144 | 0.4950 | 0.9900 | 0.9900 | nan | 0.9900 | 0.0 | 0.9900 |
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+ | 0.0151 | 4.87 | 1700 | 0.0143 | 0.4956 | 0.9911 | 0.9911 | nan | 0.9911 | 0.0 | 0.9911 |
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+ | 0.0211 | 4.93 | 1720 | 0.0149 | 0.4965 | 0.9930 | 0.9930 | nan | 0.9930 | 0.0 | 0.9930 |
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+ | 0.0136 | 4.99 | 1740 | 0.0144 | 0.4964 | 0.9928 | 0.9928 | nan | 0.9928 | 0.0 | 0.9928 |
145
+ | 0.0129 | 5.04 | 1760 | 0.0142 | 0.4967 | 0.9934 | 0.9934 | nan | 0.9934 | 0.0 | 0.9934 |
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+ | 0.0176 | 5.1 | 1780 | 0.0142 | 0.4965 | 0.9930 | 0.9930 | nan | 0.9930 | 0.0 | 0.9930 |
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+ | 0.0119 | 5.16 | 1800 | 0.0141 | 0.4958 | 0.9916 | 0.9916 | nan | 0.9916 | 0.0 | 0.9916 |
148
+ | 0.021 | 5.21 | 1820 | 0.0143 | 0.4960 | 0.9920 | 0.9920 | nan | 0.9920 | 0.0 | 0.9920 |
149
+ | 0.0146 | 5.27 | 1840 | 0.0137 | 0.4961 | 0.9922 | 0.9922 | nan | 0.9922 | 0.0 | 0.9922 |
150
+ | 0.0158 | 5.33 | 1860 | 0.0138 | 0.4953 | 0.9905 | 0.9905 | nan | 0.9905 | 0.0 | 0.9905 |
151
+ | 0.014 | 5.39 | 1880 | 0.0142 | 0.4956 | 0.9913 | 0.9913 | nan | 0.9913 | 0.0 | 0.9913 |
152
+ | 0.0145 | 5.44 | 1900 | 0.0145 | 0.4952 | 0.9905 | 0.9905 | nan | 0.9905 | 0.0 | 0.9905 |
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+ | 0.019 | 5.5 | 1920 | 0.0145 | 0.4960 | 0.9920 | 0.9920 | nan | 0.9920 | 0.0 | 0.9920 |
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+ | 0.0134 | 5.56 | 1940 | 0.0143 | 0.4958 | 0.9915 | 0.9915 | nan | 0.9915 | 0.0 | 0.9915 |
155
+ | 0.011 | 5.62 | 1960 | 0.0141 | 0.4955 | 0.9910 | 0.9910 | nan | 0.9910 | 0.0 | 0.9910 |
156
+ | 0.0159 | 5.67 | 1980 | 0.0143 | 0.4971 | 0.9942 | 0.9942 | nan | 0.9942 | 0.0 | 0.9942 |
157
+ | 0.0132 | 5.73 | 2000 | 0.0140 | 0.4966 | 0.9933 | 0.9933 | nan | 0.9933 | 0.0 | 0.9933 |
158
+ | 0.017 | 5.79 | 2020 | 0.0136 | 0.4964 | 0.9928 | 0.9928 | nan | 0.9928 | 0.0 | 0.9928 |
159
+ | 0.0156 | 5.85 | 2040 | 0.0139 | 0.4951 | 0.9902 | 0.9902 | nan | 0.9902 | 0.0 | 0.9902 |
160
+ | 0.0169 | 5.9 | 2060 | 0.0142 | 0.4943 | 0.9887 | 0.9887 | nan | 0.9887 | 0.0 | 0.9887 |
161
+ | 0.0337 | 5.96 | 2080 | 0.0145 | 0.4967 | 0.9933 | 0.9933 | nan | 0.9933 | 0.0 | 0.9933 |
162
+ | 0.0158 | 6.02 | 2100 | 0.0141 | 0.4949 | 0.9898 | 0.9898 | nan | 0.9898 | 0.0 | 0.9898 |
163
+ | 0.0401 | 6.07 | 2120 | 0.0139 | 0.4956 | 0.9912 | 0.9912 | nan | 0.9912 | 0.0 | 0.9912 |
164
+ | 0.0629 | 6.13 | 2140 | 0.0138 | 0.4952 | 0.9904 | 0.9904 | nan | 0.9904 | 0.0 | 0.9904 |
165
+ | 0.0143 | 6.19 | 2160 | 0.0142 | 0.4967 | 0.9935 | 0.9935 | nan | 0.9935 | 0.0 | 0.9935 |
166
+ | 0.0133 | 6.25 | 2180 | 0.0135 | 0.4957 | 0.9915 | 0.9915 | nan | 0.9915 | 0.0 | 0.9915 |
167
+ | 0.0326 | 6.3 | 2200 | 0.0139 | 0.4963 | 0.9925 | 0.9925 | nan | 0.9925 | 0.0 | 0.9925 |
168
+ | 0.0141 | 6.36 | 2220 | 0.0133 | 0.4955 | 0.9910 | 0.9910 | nan | 0.9910 | 0.0 | 0.9910 |
169
+ | 0.0119 | 6.42 | 2240 | 0.0134 | 0.4958 | 0.9915 | 0.9915 | nan | 0.9915 | 0.0 | 0.9915 |
170
+ | 0.0133 | 6.48 | 2260 | 0.0139 | 0.4962 | 0.9924 | 0.9924 | nan | 0.9924 | 0.0 | 0.9924 |
171
+ | 0.0123 | 6.53 | 2280 | 0.0138 | 0.4967 | 0.9934 | 0.9934 | nan | 0.9934 | 0.0 | 0.9934 |
172
+ | 0.014 | 6.59 | 2300 | 0.0138 | 0.4962 | 0.9925 | 0.9925 | nan | 0.9925 | 0.0 | 0.9925 |
173
+ | 0.0137 | 6.65 | 2320 | 0.0136 | 0.4958 | 0.9916 | 0.9916 | nan | 0.9916 | 0.0 | 0.9916 |
174
+ | 0.0173 | 6.7 | 2340 | 0.0138 | 0.4964 | 0.9928 | 0.9928 | nan | 0.9928 | 0.0 | 0.9928 |
175
+ | 0.0137 | 6.76 | 2360 | 0.0136 | 0.4953 | 0.9905 | 0.9905 | nan | 0.9905 | 0.0 | 0.9905 |
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+ | 0.0153 | 6.82 | 2380 | 0.0134 | 0.4958 | 0.9916 | 0.9916 | nan | 0.9916 | 0.0 | 0.9916 |
177
+ | 0.0135 | 6.88 | 2400 | 0.0137 | 0.4963 | 0.9926 | 0.9926 | nan | 0.9926 | 0.0 | 0.9926 |
178
+ | 0.0151 | 6.93 | 2420 | 0.0137 | 0.4952 | 0.9904 | 0.9904 | nan | 0.9904 | 0.0 | 0.9904 |
179
+ | 0.0122 | 6.99 | 2440 | 0.0134 | 0.4959 | 0.9918 | 0.9918 | nan | 0.9918 | 0.0 | 0.9918 |
180
+ | 0.013 | 7.05 | 2460 | 0.0135 | 0.4970 | 0.9941 | 0.9941 | nan | 0.9941 | 0.0 | 0.9941 |
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+ | 0.0134 | 7.11 | 2480 | 0.0133 | 0.4964 | 0.9928 | 0.9928 | nan | 0.9928 | 0.0 | 0.9928 |
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+ | 0.0145 | 7.16 | 2500 | 0.0134 | 0.4962 | 0.9924 | 0.9924 | nan | 0.9924 | 0.0 | 0.9924 |
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+ | 0.028 | 7.22 | 2520 | 0.0135 | 0.4962 | 0.9924 | 0.9924 | nan | 0.9924 | 0.0 | 0.9924 |
184
+ | 0.0288 | 7.28 | 2540 | 0.0137 | 0.4967 | 0.9933 | 0.9933 | nan | 0.9933 | 0.0 | 0.9933 |
185
+ | 0.0117 | 7.34 | 2560 | 0.0135 | 0.4964 | 0.9927 | 0.9927 | nan | 0.9927 | 0.0 | 0.9927 |
186
+ | 0.013 | 7.39 | 2580 | 0.0136 | 0.4966 | 0.9932 | 0.9932 | nan | 0.9932 | 0.0 | 0.9932 |
187
+ | 0.0158 | 7.45 | 2600 | 0.0134 | 0.4950 | 0.9899 | 0.9899 | nan | 0.9899 | 0.0 | 0.9899 |
188
+ | 0.0135 | 7.51 | 2620 | 0.0134 | 0.4964 | 0.9928 | 0.9928 | nan | 0.9928 | 0.0 | 0.9928 |
189
+ | 0.0136 | 7.56 | 2640 | 0.0140 | 0.4967 | 0.9935 | 0.9935 | nan | 0.9935 | 0.0 | 0.9935 |
190
+ | 0.0396 | 7.62 | 2660 | 0.0133 | 0.4961 | 0.9922 | 0.9922 | nan | 0.9922 | 0.0 | 0.9922 |
191
+ | 0.0109 | 7.68 | 2680 | 0.0134 | 0.4963 | 0.9925 | 0.9925 | nan | 0.9925 | 0.0 | 0.9925 |
192
+ | 0.0148 | 7.74 | 2700 | 0.0133 | 0.4963 | 0.9925 | 0.9925 | nan | 0.9925 | 0.0 | 0.9925 |
193
+ | 0.0121 | 7.79 | 2720 | 0.0140 | 0.4945 | 0.9890 | 0.9890 | nan | 0.9890 | 0.0 | 0.9890 |
194
+ | 0.0109 | 7.85 | 2740 | 0.0139 | 0.4957 | 0.9913 | 0.9913 | nan | 0.9913 | 0.0 | 0.9913 |
195
+ | 0.014 | 7.91 | 2760 | 0.0135 | 0.4957 | 0.9915 | 0.9915 | nan | 0.9915 | 0.0 | 0.9915 |
196
+ | 0.0199 | 7.97 | 2780 | 0.0134 | 0.4959 | 0.9917 | 0.9917 | nan | 0.9917 | 0.0 | 0.9917 |
197
+ | 0.0119 | 8.02 | 2800 | 0.0136 | 0.4958 | 0.9916 | 0.9916 | nan | 0.9916 | 0.0 | 0.9916 |
198
+ | 0.0129 | 8.08 | 2820 | 0.0136 | 0.4962 | 0.9924 | 0.9924 | nan | 0.9924 | 0.0 | 0.9924 |
199
+ | 0.0108 | 8.14 | 2840 | 0.0134 | 0.4959 | 0.9917 | 0.9917 | nan | 0.9917 | 0.0 | 0.9917 |
200
+ | 0.0209 | 8.19 | 2860 | 0.0136 | 0.4960 | 0.9920 | 0.9920 | nan | 0.9920 | 0.0 | 0.9920 |
201
+ | 0.0154 | 8.25 | 2880 | 0.0137 | 0.4964 | 0.9928 | 0.9928 | nan | 0.9928 | 0.0 | 0.9928 |
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+ | 0.0141 | 8.31 | 2900 | 0.0132 | 0.4965 | 0.9929 | 0.9929 | nan | 0.9929 | 0.0 | 0.9929 |
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+ | 0.0187 | 8.37 | 2920 | 0.0131 | 0.4956 | 0.9912 | 0.9912 | nan | 0.9912 | 0.0 | 0.9912 |
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+ | 0.0124 | 8.42 | 2940 | 0.0133 | 0.4959 | 0.9918 | 0.9918 | nan | 0.9918 | 0.0 | 0.9918 |
205
+ | 0.0135 | 8.48 | 2960 | 0.0132 | 0.4963 | 0.9926 | 0.9926 | nan | 0.9926 | 0.0 | 0.9926 |
206
+ | 0.0283 | 8.54 | 2980 | 0.0131 | 0.4958 | 0.9917 | 0.9917 | nan | 0.9917 | 0.0 | 0.9917 |
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+ | 0.0691 | 8.6 | 3000 | 0.0131 | 0.4965 | 0.9930 | 0.9930 | nan | 0.9930 | 0.0 | 0.9930 |
208
+ | 0.0142 | 8.65 | 3020 | 0.0131 | 0.4965 | 0.9929 | 0.9929 | nan | 0.9929 | 0.0 | 0.9929 |
209
+ | 0.0155 | 8.71 | 3040 | 0.0130 | 0.4966 | 0.9931 | 0.9931 | nan | 0.9931 | 0.0 | 0.9931 |
210
+ | 0.0115 | 8.77 | 3060 | 0.0129 | 0.4966 | 0.9932 | 0.9932 | nan | 0.9932 | 0.0 | 0.9932 |
211
+ | 0.0095 | 8.83 | 3080 | 0.0130 | 0.4963 | 0.9927 | 0.9927 | nan | 0.9927 | 0.0 | 0.9927 |
212
+ | 0.012 | 8.88 | 3100 | 0.0132 | 0.4954 | 0.9907 | 0.9907 | nan | 0.9907 | 0.0 | 0.9907 |
213
+ | 0.0153 | 8.94 | 3120 | 0.0132 | 0.4965 | 0.9930 | 0.9930 | nan | 0.9930 | 0.0 | 0.9930 |
214
+ | 0.0141 | 9.0 | 3140 | 0.0134 | 0.4958 | 0.9917 | 0.9917 | nan | 0.9917 | 0.0 | 0.9917 |
215
+ | 0.0141 | 9.05 | 3160 | 0.0133 | 0.4958 | 0.9915 | 0.9915 | nan | 0.9915 | 0.0 | 0.9915 |
216
+ | 0.016 | 9.11 | 3180 | 0.0133 | 0.4964 | 0.9929 | 0.9929 | nan | 0.9929 | 0.0 | 0.9929 |
217
+ | 0.017 | 9.17 | 3200 | 0.0132 | 0.4965 | 0.9929 | 0.9929 | nan | 0.9929 | 0.0 | 0.9929 |
218
+ | 0.0245 | 9.23 | 3220 | 0.0132 | 0.4961 | 0.9921 | 0.9921 | nan | 0.9921 | 0.0 | 0.9921 |
219
+ | 0.0101 | 9.28 | 3240 | 0.0132 | 0.4962 | 0.9924 | 0.9924 | nan | 0.9924 | 0.0 | 0.9924 |
220
+ | 0.012 | 9.34 | 3260 | 0.0133 | 0.4959 | 0.9917 | 0.9917 | nan | 0.9917 | 0.0 | 0.9917 |
221
+ | 0.0111 | 9.4 | 3280 | 0.0133 | 0.4964 | 0.9928 | 0.9928 | nan | 0.9928 | 0.0 | 0.9928 |
222
+ | 0.0148 | 9.46 | 3300 | 0.0132 | 0.4962 | 0.9925 | 0.9925 | nan | 0.9925 | 0.0 | 0.9925 |
223
+ | 0.0124 | 9.51 | 3320 | 0.0135 | 0.4967 | 0.9934 | 0.9934 | nan | 0.9934 | 0.0 | 0.9934 |
224
+ | 0.0209 | 9.57 | 3340 | 0.0133 | 0.4963 | 0.9926 | 0.9926 | nan | 0.9926 | 0.0 | 0.9926 |
225
+ | 0.0134 | 9.63 | 3360 | 0.0132 | 0.4960 | 0.9920 | 0.9920 | nan | 0.9920 | 0.0 | 0.9920 |
226
+ | 0.0146 | 9.68 | 3380 | 0.0132 | 0.4958 | 0.9916 | 0.9916 | nan | 0.9916 | 0.0 | 0.9916 |
227
+ | 0.0217 | 9.74 | 3400 | 0.0132 | 0.4961 | 0.9923 | 0.9923 | nan | 0.9923 | 0.0 | 0.9923 |
228
+ | 0.0142 | 9.8 | 3420 | 0.0131 | 0.4961 | 0.9923 | 0.9923 | nan | 0.9923 | 0.0 | 0.9923 |
229
+ | 0.0134 | 9.86 | 3440 | 0.0131 | 0.4959 | 0.9918 | 0.9918 | nan | 0.9918 | 0.0 | 0.9918 |
230
+ | 0.0131 | 9.91 | 3460 | 0.0131 | 0.4960 | 0.9920 | 0.9920 | nan | 0.9920 | 0.0 | 0.9920 |
231
+ | 0.0136 | 9.97 | 3480 | 0.0131 | 0.4961 | 0.9922 | 0.9922 | nan | 0.9922 | 0.0 | 0.9922 |
232
+
233
+
234
+ ### Framework versions
235
+
236
+ - Transformers 4.35.0
237
+ - Pytorch 2.2.2
238
+ - Datasets 2.14.6
239
+ - Tokenizers 0.14.1
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