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myclassification

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Safetensors
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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ library_name: peft
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - accuracy
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+ base_model: distilbert-base-uncased
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+ model-index:
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+ - name: myclassification
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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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+ # myclassification
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+
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+ This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1432
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+ - Accuracy: 0.9388
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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: 5e-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: 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: 100
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:-----:|:---------------:|:--------:|
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+ | 0.6881 | 1.0 | 625 | 0.5453 | 0.7528 |
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+ | 0.5585 | 2.0 | 1250 | 0.4954 | 0.7574 |
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+ | 0.5185 | 3.0 | 1875 | 0.4485 | 0.8018 |
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+ | 0.4635 | 4.0 | 2500 | 0.4274 | 0.8236 |
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+ | 0.4556 | 5.0 | 3125 | 0.4262 | 0.8264 |
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+ | 0.431 | 6.0 | 3750 | 0.4520 | 0.8258 |
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+ | 0.4422 | 7.0 | 4375 | 0.4324 | 0.829 |
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+ | 0.4276 | 8.0 | 5000 | 0.3828 | 0.8342 |
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+ | 0.4137 | 9.0 | 5625 | 0.4053 | 0.8306 |
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+ | 0.4282 | 10.0 | 6250 | 0.3915 | 0.834 |
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+ | 0.4131 | 11.0 | 6875 | 0.4001 | 0.8342 |
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+ | 0.403 | 12.0 | 7500 | 0.3894 | 0.834 |
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+ | 0.4098 | 13.0 | 8125 | 0.3739 | 0.8352 |
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+ | 0.3976 | 14.0 | 8750 | 0.3936 | 0.8298 |
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+ | 0.4015 | 15.0 | 9375 | 0.3794 | 0.836 |
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+ | 0.3979 | 16.0 | 10000 | 0.3737 | 0.841 |
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+ | 0.3894 | 17.0 | 10625 | 0.3610 | 0.8364 |
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+ | 0.3884 | 18.0 | 11250 | 0.3530 | 0.8312 |
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+ | 0.3852 | 19.0 | 11875 | 0.3564 | 0.8348 |
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+ | 0.3806 | 20.0 | 12500 | 0.3507 | 0.842 |
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+ | 0.3803 | 21.0 | 13125 | 0.3439 | 0.8392 |
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+ | 0.3757 | 22.0 | 13750 | 0.3391 | 0.8386 |
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+ | 0.37 | 23.0 | 14375 | 0.3244 | 0.8428 |
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+ | 0.3781 | 24.0 | 15000 | 0.3200 | 0.8442 |
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+ | 0.3662 | 25.0 | 15625 | 0.3418 | 0.8458 |
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+ | 0.3515 | 26.0 | 16250 | 0.3043 | 0.8522 |
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+ | 0.3615 | 27.0 | 16875 | 0.2973 | 0.8606 |
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+ | 0.3532 | 28.0 | 17500 | 0.3105 | 0.8558 |
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+ | 0.3498 | 29.0 | 18125 | 0.2971 | 0.8664 |
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+ | 0.3564 | 30.0 | 18750 | 0.3051 | 0.8684 |
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+ | 0.3469 | 31.0 | 19375 | 0.3050 | 0.8688 |
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+ | 0.349 | 32.0 | 20000 | 0.2813 | 0.864 |
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+ | 0.3294 | 33.0 | 20625 | 0.2898 | 0.8716 |
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+ | 0.3371 | 34.0 | 21250 | 0.2921 | 0.8728 |
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+ | 0.3254 | 35.0 | 21875 | 0.2812 | 0.8744 |
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+ | 0.3382 | 36.0 | 22500 | 0.2816 | 0.8622 |
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+ | 0.3402 | 37.0 | 23125 | 0.2905 | 0.873 |
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+ | 0.3333 | 38.0 | 23750 | 0.2832 | 0.863 |
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+ | 0.3084 | 39.0 | 24375 | 0.3017 | 0.8734 |
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+ | 0.3421 | 40.0 | 25000 | 0.2876 | 0.8718 |
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+ | 0.3113 | 41.0 | 25625 | 0.2759 | 0.8642 |
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+ | 0.3223 | 42.0 | 26250 | 0.2814 | 0.8746 |
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+ | 0.3154 | 43.0 | 26875 | 0.2691 | 0.8684 |
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+ | 0.3185 | 44.0 | 27500 | 0.2780 | 0.8726 |
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+ | 0.3074 | 45.0 | 28125 | 0.2596 | 0.88 |
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+ | 0.3037 | 46.0 | 28750 | 0.2645 | 0.8822 |
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+ | 0.3035 | 47.0 | 29375 | 0.2498 | 0.8848 |
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+ | 0.3144 | 48.0 | 30000 | 0.2552 | 0.8742 |
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+ | 0.3057 | 49.0 | 30625 | 0.2453 | 0.8876 |
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+ | 0.2972 | 50.0 | 31250 | 0.2412 | 0.891 |
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+ | 0.2962 | 51.0 | 31875 | 0.2394 | 0.8938 |
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+ | 0.2931 | 52.0 | 32500 | 0.2502 | 0.8948 |
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+ | 0.2908 | 53.0 | 33125 | 0.2398 | 0.8972 |
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+ | 0.288 | 54.0 | 33750 | 0.2314 | 0.8972 |
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+ | 0.2872 | 55.0 | 34375 | 0.2221 | 0.9016 |
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+ | 0.2885 | 56.0 | 35000 | 0.2404 | 0.8932 |
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+ | 0.2828 | 57.0 | 35625 | 0.2145 | 0.9046 |
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+ | 0.2786 | 58.0 | 36250 | 0.2171 | 0.9038 |
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+ | 0.267 | 59.0 | 36875 | 0.2191 | 0.9062 |
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+ | 0.2689 | 60.0 | 37500 | 0.2012 | 0.9084 |
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+ | 0.2716 | 61.0 | 38125 | 0.2061 | 0.9096 |
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+ | 0.2707 | 62.0 | 38750 | 0.2156 | 0.912 |
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+ | 0.275 | 63.0 | 39375 | 0.1997 | 0.911 |
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+ | 0.2355 | 64.0 | 40000 | 0.1991 | 0.9128 |
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+ | 0.2692 | 65.0 | 40625 | 0.1910 | 0.914 |
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+ | 0.2591 | 66.0 | 41250 | 0.1833 | 0.9166 |
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+ | 0.2694 | 67.0 | 41875 | 0.1838 | 0.9228 |
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+ | 0.2762 | 68.0 | 42500 | 0.1776 | 0.9244 |
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+ | 0.2596 | 69.0 | 43125 | 0.1820 | 0.924 |
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+ | 0.2624 | 70.0 | 43750 | 0.1893 | 0.9218 |
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+ | 0.2442 | 71.0 | 44375 | 0.1764 | 0.9234 |
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+ | 0.2601 | 72.0 | 45000 | 0.1652 | 0.9292 |
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+ | 0.2614 | 73.0 | 45625 | 0.1701 | 0.9232 |
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+ | 0.2579 | 74.0 | 46250 | 0.1627 | 0.9308 |
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+ | 0.2562 | 75.0 | 46875 | 0.1616 | 0.9306 |
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+ | 0.244 | 76.0 | 47500 | 0.1630 | 0.9312 |
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+ | 0.2368 | 77.0 | 48125 | 0.1616 | 0.9298 |
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+ | 0.2619 | 78.0 | 48750 | 0.1658 | 0.93 |
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+ | 0.2249 | 79.0 | 49375 | 0.1596 | 0.9316 |
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+ | 0.254 | 80.0 | 50000 | 0.1525 | 0.9334 |
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+ | 0.2467 | 81.0 | 50625 | 0.1596 | 0.9336 |
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+ | 0.2311 | 82.0 | 51250 | 0.1577 | 0.932 |
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+ | 0.2422 | 83.0 | 51875 | 0.1502 | 0.9346 |
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+ | 0.2224 | 84.0 | 52500 | 0.1500 | 0.9358 |
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+ | 0.2377 | 85.0 | 53125 | 0.1499 | 0.937 |
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+ | 0.2442 | 86.0 | 53750 | 0.1498 | 0.9364 |
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+ | 0.2285 | 87.0 | 54375 | 0.1506 | 0.9354 |
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+ | 0.2361 | 88.0 | 55000 | 0.1479 | 0.9362 |
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+ | 0.2416 | 89.0 | 55625 | 0.1461 | 0.9372 |
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+ | 0.2315 | 90.0 | 56250 | 0.1462 | 0.9362 |
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+ | 0.2282 | 91.0 | 56875 | 0.1471 | 0.9348 |
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+ | 0.2293 | 92.0 | 57500 | 0.1479 | 0.9348 |
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+ | 0.2246 | 93.0 | 58125 | 0.1484 | 0.9376 |
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+ | 0.2568 | 94.0 | 58750 | 0.1434 | 0.9384 |
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+ | 0.2356 | 95.0 | 59375 | 0.1454 | 0.9374 |
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+ | 0.2357 | 96.0 | 60000 | 0.1432 | 0.9378 |
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+ | 0.2301 | 97.0 | 60625 | 0.1421 | 0.9386 |
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+ | 0.2321 | 98.0 | 61250 | 0.1425 | 0.9386 |
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+ | 0.241 | 99.0 | 61875 | 0.1427 | 0.9392 |
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+ | 0.2283 | 100.0 | 62500 | 0.1432 | 0.9388 |
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+
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+
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+ ### Framework versions
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+
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+ - PEFT 0.8.2
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+ - Transformers 4.39.0.dev0
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+ - Pytorch 2.1.0+cu121
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+ - Datasets 2.17.1
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+ - Tokenizers 0.15.2
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