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shanthi-323
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fine-tuned-bert-CBT

Text Classification
Transformers
Safetensors
bert
Generated from Trainer
Inference Endpoints
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+ ---
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+ library_name: transformers
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+ license: apache-2.0
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+ base_model: bert-base-uncased
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: fine-tuned-bert-CBT
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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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+ # fine-tuned-bert-CBT
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+
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+ This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.9580
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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: 2e-05
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+ - train_batch_size: 8
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: linear
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+ - num_epochs: 3
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:------:|:----:|:---------------:|
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+ | 2.6996 | 0.0278 | 10 | 2.5932 |
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+ | 2.5659 | 0.0556 | 20 | 2.4949 |
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+ | 2.5146 | 0.0833 | 30 | 2.3969 |
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+ | 2.4268 | 0.1111 | 40 | 2.3803 |
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+ | 2.3637 | 0.1389 | 50 | 2.2703 |
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+ | 2.2599 | 0.1667 | 60 | 2.2429 |
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+ | 2.2562 | 0.1944 | 70 | 2.1078 |
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+ | 2.0763 | 0.2222 | 80 | 2.0618 |
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+ | 2.0285 | 0.25 | 90 | 2.0001 |
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+ | 2.0964 | 0.2778 | 100 | 1.9234 |
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+ | 1.8736 | 0.3056 | 110 | 1.8622 |
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+ | 1.9762 | 0.3333 | 120 | 1.8228 |
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+ | 1.8524 | 0.3611 | 130 | 1.7528 |
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+ | 1.7582 | 0.3889 | 140 | 1.6850 |
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+ | 1.666 | 0.4167 | 150 | 1.6393 |
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+ | 1.6081 | 0.4444 | 160 | 1.5788 |
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+ | 1.5763 | 0.4722 | 170 | 1.5264 |
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+ | 1.5569 | 0.5 | 180 | 1.5205 |
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+ | 1.5338 | 0.5278 | 190 | 1.4746 |
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+ | 1.3994 | 0.5556 | 200 | 1.4834 |
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+ | 1.4633 | 0.5833 | 210 | 1.4261 |
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+ | 1.5346 | 0.6111 | 220 | 1.3530 |
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+ | 1.4419 | 0.6389 | 230 | 1.3255 |
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+ | 1.2908 | 0.6667 | 240 | 1.3178 |
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+ | 1.4339 | 0.6944 | 250 | 1.3066 |
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+ | 1.2745 | 0.7222 | 260 | 1.2494 |
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+ | 1.3522 | 0.75 | 270 | 1.2489 |
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+ | 1.2186 | 0.7778 | 280 | 1.2322 |
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+ | 1.2945 | 0.8056 | 290 | 1.1780 |
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+ | 1.3717 | 0.8333 | 300 | 1.2243 |
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+ | 1.2835 | 0.8611 | 310 | 1.2065 |
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+ | 1.2402 | 0.8889 | 320 | 1.1678 |
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+ | 1.0937 | 0.9167 | 330 | 1.1325 |
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+ | 1.2552 | 0.9444 | 340 | 1.1202 |
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+ | 1.1272 | 0.9722 | 350 | 1.1032 |
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+ | 1.1746 | 1.0 | 360 | 1.0993 |
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+ | 1.1314 | 1.0278 | 370 | 1.0908 |
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+ | 1.1143 | 1.0556 | 380 | 1.0849 |
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+ | 0.9685 | 1.0833 | 390 | 1.0890 |
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+ | 0.8647 | 1.1111 | 400 | 1.1004 |
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+ | 0.8987 | 1.1389 | 410 | 1.0898 |
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+ | 0.8619 | 1.1667 | 420 | 1.1206 |
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+ | 0.8827 | 1.1944 | 430 | 1.0759 |
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+ | 0.9164 | 1.2222 | 440 | 1.0875 |
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+ | 1.1161 | 1.25 | 450 | 1.0763 |
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+ | 0.8902 | 1.2778 | 460 | 1.0525 |
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+ | 0.9228 | 1.3056 | 470 | 1.0476 |
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+ | 0.789 | 1.3333 | 480 | 1.0377 |
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+ | 0.8984 | 1.3611 | 490 | 1.0522 |
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+ | 1.065 | 1.3889 | 500 | 1.0215 |
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+ | 0.7046 | 1.4167 | 510 | 1.0186 |
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+ | 0.9612 | 1.4444 | 520 | 1.0143 |
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+ | 0.7705 | 1.4722 | 530 | 1.0207 |
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+ | 0.7768 | 1.5 | 540 | 1.0060 |
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+ | 1.0041 | 1.5278 | 550 | 1.0296 |
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+ | 1.0711 | 1.5556 | 560 | 1.0030 |
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+ | 0.6894 | 1.5833 | 570 | 1.0044 |
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+ | 1.1434 | 1.6111 | 580 | 0.9944 |
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+ | 0.9194 | 1.6389 | 590 | 0.9822 |
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+ | 0.8456 | 1.6667 | 600 | 0.9993 |
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+ | 0.8691 | 1.6944 | 610 | 0.9917 |
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+ | 0.8099 | 1.7222 | 620 | 0.9836 |
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+ | 0.9797 | 1.75 | 630 | 0.9814 |
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+ | 0.9307 | 1.7778 | 640 | 0.9790 |
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+ | 0.6684 | 1.8056 | 650 | 0.9704 |
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+ | 0.8533 | 1.8333 | 660 | 0.9869 |
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+ | 0.8324 | 1.8611 | 670 | 0.9658 |
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+ | 0.7872 | 1.8889 | 680 | 0.9683 |
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+ | 0.6827 | 1.9167 | 690 | 0.9857 |
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+ | 1.0274 | 1.9444 | 700 | 0.9893 |
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+ | 0.8892 | 1.9722 | 710 | 0.9738 |
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+ | 0.7447 | 2.0 | 720 | 0.9732 |
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+ | 0.7072 | 2.0278 | 730 | 0.9748 |
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+ | 0.7205 | 2.0556 | 740 | 0.9637 |
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+ | 0.6102 | 2.0833 | 750 | 0.9647 |
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+ | 0.7017 | 2.1111 | 760 | 0.9520 |
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+ | 0.7374 | 2.1389 | 770 | 0.9495 |
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+ | 0.6856 | 2.1667 | 780 | 0.9455 |
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+ | 0.4585 | 2.1944 | 790 | 0.9481 |
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+ | 0.5872 | 2.2222 | 800 | 0.9494 |
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+ | 0.7054 | 2.25 | 810 | 0.9457 |
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+ | 0.7 | 2.2778 | 820 | 0.9557 |
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+ | 0.5781 | 2.3056 | 830 | 0.9579 |
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+ | 0.6319 | 2.3333 | 840 | 0.9677 |
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+ | 0.5814 | 2.3611 | 850 | 0.9705 |
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+ | 0.5985 | 2.3889 | 860 | 0.9614 |
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+ | 0.729 | 2.4167 | 870 | 0.9536 |
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+ | 0.6084 | 2.4444 | 880 | 0.9499 |
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+ | 0.755 | 2.4722 | 890 | 0.9594 |
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+ | 0.4991 | 2.5 | 900 | 0.9782 |
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+ | 0.5469 | 2.5278 | 910 | 0.9928 |
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+ | 0.6299 | 2.5556 | 920 | 0.9875 |
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+ | 0.5911 | 2.5833 | 930 | 0.9720 |
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+ | 0.4386 | 2.6111 | 940 | 0.9701 |
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+ | 0.5477 | 2.6389 | 950 | 0.9695 |
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+ | 0.6532 | 2.6667 | 960 | 0.9723 |
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+ | 0.6322 | 2.6944 | 970 | 0.9710 |
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+ | 0.4968 | 2.7222 | 980 | 0.9701 |
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+ | 0.5498 | 2.75 | 990 | 0.9708 |
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+ | 0.746 | 2.7778 | 1000 | 0.9697 |
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+ | 0.5654 | 2.8056 | 1010 | 0.9698 |
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+ | 0.5468 | 2.8333 | 1020 | 0.9655 |
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+ | 0.6086 | 2.8611 | 1030 | 0.9643 |
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+ | 0.6928 | 2.8889 | 1040 | 0.9612 |
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+ | 0.4775 | 2.9167 | 1050 | 0.9585 |
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+ | 0.5934 | 2.9444 | 1060 | 0.9579 |
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+ | 0.6645 | 2.9722 | 1070 | 0.9580 |
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+ | 0.5721 | 3.0 | 1080 | 0.9580 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.47.0
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+ - Pytorch 2.5.1+cu121
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+ - Datasets 3.1.0
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+ - Tokenizers 0.21.0