End of training
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README.md
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---
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license: apache-2.0
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base_model: distilbert/distilbert-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: my_awesome_qa_model
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results: []
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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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# my_awesome_qa_model
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This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/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: 1.3052
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 2e-07
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- train_batch_size: 32
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- eval_batch_size: 32
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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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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:-----:|:------:|:---------------:|
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| 4.6796 | 1.0 | 2190 | 4.4264 |
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| 3.9385 | 2.0 | 4380 | 3.7109 |
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| 3.3803 | 3.0 | 6570 | 3.2006 |
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| 3.0145 | 4.0 | 8760 | 2.7950 |
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| 2.7776 | 5.0 | 10950 | 2.5765 |
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| 2.595 | 6.0 | 13140 | 2.4387 |
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| 2.4978 | 7.0 | 15330 | 2.3404 |
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| 2.3957 | 8.0 | 17520 | 2.2612 |
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| 2.3229 | 9.0 | 19710 | 2.1812 |
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| 2.2338 | 10.0 | 21900 | 2.0971 |
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| 2.1596 | 11.0 | 24090 | 2.0173 |
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| 2.0972 | 12.0 | 26280 | 1.9428 |
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| 2.0085 | 13.0 | 28470 | 1.8775 |
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| 1.9591 | 14.0 | 30660 | 1.8191 |
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| 1.9021 | 15.0 | 32850 | 1.7753 |
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| 1.8743 | 16.0 | 35040 | 1.7351 |
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| 1.8223 | 17.0 | 37230 | 1.7036 |
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| 1.8064 | 18.0 | 39420 | 1.6734 |
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| 1.7535 | 19.0 | 41610 | 1.6507 |
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| 1.7349 | 20.0 | 43800 | 1.6266 |
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| 1.7017 | 21.0 | 45990 | 1.6077 |
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| 1.6698 | 22.0 | 48180 | 1.5890 |
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| 1.6592 | 23.0 | 50370 | 1.5778 |
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| 1.6407 | 24.0 | 52560 | 1.5616 |
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| 1.6127 | 25.0 | 54750 | 1.5478 |
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| 1.6082 | 26.0 | 56940 | 1.5328 |
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| 1.5979 | 27.0 | 59130 | 1.5232 |
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| 1.5655 | 28.0 | 61320 | 1.5127 |
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| 1.5408 | 29.0 | 63510 | 1.5034 |
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| 1.5523 | 30.0 | 65700 | 1.4931 |
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| 1.5291 | 31.0 | 67890 | 1.4841 |
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| 1.527 | 32.0 | 70080 | 1.4731 |
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| 1.5099 | 33.0 | 72270 | 1.4676 |
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| 1.4846 | 34.0 | 74460 | 1.4564 |
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| 1.4928 | 35.0 | 76650 | 1.4504 |
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| 1.4743 | 36.0 | 78840 | 1.4432 |
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| 1.4605 | 37.0 | 81030 | 1.4395 |
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| 1.452 | 38.0 | 83220 | 1.4314 |
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| 1.4617 | 39.0 | 85410 | 1.4257 |
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| 1.4633 | 40.0 | 87600 | 1.4198 |
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| 1.4551 | 41.0 | 89790 | 1.4143 |
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| 1.4227 | 42.0 | 91980 | 1.4074 |
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| 1.4208 | 43.0 | 94170 | 1.4050 |
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| 1.4008 | 44.0 | 96360 | 1.3999 |
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| 1.4075 | 45.0 | 98550 | 1.3966 |
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| 1.4032 | 46.0 | 100740 | 1.3916 |
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| 1.368 | 47.0 | 102930 | 1.3884 |
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| 1.3802 | 48.0 | 105120 | 1.3843 |
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| 1.3914 | 49.0 | 107310 | 1.3807 |
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| 1.3692 | 50.0 | 109500 | 1.3765 |
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| 1.3698 | 51.0 | 111690 | 1.3722 |
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| 1.3597 | 52.0 | 113880 | 1.3684 |
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| 1.3551 | 53.0 | 116070 | 1.3663 |
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| 1.3498 | 54.0 | 118260 | 1.3628 |
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| 1.3428 | 55.0 | 120450 | 1.3608 |
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| 1.3367 | 56.0 | 122640 | 1.3573 |
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| 1.3202 | 57.0 | 124830 | 1.3549 |
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| 1.346 | 58.0 | 127020 | 1.3499 |
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| 1.3268 | 59.0 | 129210 | 1.3488 |
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| 1.3253 | 60.0 | 131400 | 1.3468 |
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| 1.3132 | 61.0 | 133590 | 1.3438 |
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| 1.3247 | 62.0 | 135780 | 1.3425 |
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| 1.3222 | 63.0 | 137970 | 1.3397 |
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| 1.3045 | 64.0 | 140160 | 1.3381 |
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| 1.3096 | 65.0 | 142350 | 1.3345 |
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| 1.3131 | 66.0 | 144540 | 1.3334 |
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| 1.284 | 67.0 | 146730 | 1.3331 |
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| 1.2991 | 68.0 | 148920 | 1.3294 |
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| 1.2794 | 69.0 | 151110 | 1.3280 |
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| 1.2992 | 70.0 | 153300 | 1.3278 |
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| 1.2884 | 71.0 | 155490 | 1.3259 |
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| 1.2934 | 72.0 | 157680 | 1.3235 |
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| 1.2778 | 73.0 | 159870 | 1.3222 |
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| 1.2771 | 74.0 | 162060 | 1.3205 |
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| 1.2846 | 75.0 | 164250 | 1.3190 |
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| 1.2666 | 76.0 | 166440 | 1.3193 |
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| 1.2828 | 77.0 | 168630 | 1.3170 |
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| 1.2804 | 78.0 | 170820 | 1.3164 |
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| 1.283 | 79.0 | 173010 | 1.3149 |
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| 1.2621 | 80.0 | 175200 | 1.3139 |
|
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| 1.2779 | 81.0 | 177390 | 1.3136 |
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| 1.2633 | 82.0 | 179580 | 1.3125 |
|
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| 1.2596 | 83.0 | 181770 | 1.3116 |
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| 1.2653 | 84.0 | 183960 | 1.3103 |
|
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| 1.2715 | 85.0 | 186150 | 1.3088 |
|
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| 1.2553 | 86.0 | 188340 | 1.3095 |
|
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| 1.2688 | 87.0 | 190530 | 1.3093 |
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| 1.2496 | 88.0 | 192720 | 1.3086 |
|
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| 1.2683 | 89.0 | 194910 | 1.3080 |
|
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| 1.242 | 90.0 | 197100 | 1.3078 |
|
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| 1.2619 | 91.0 | 199290 | 1.3065 |
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| 1.2662 | 92.0 | 201480 | 1.3063 |
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| 1.2557 | 93.0 | 203670 | 1.3059 |
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| 1.2623 | 94.0 | 205860 | 1.3057 |
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| 1.2402 | 95.0 | 208050 | 1.3056 |
|
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| 1.2389 | 96.0 | 210240 | 1.3054 |
|
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| 1.2653 | 97.0 | 212430 | 1.3053 |
|
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| 1.2365 | 98.0 | 214620 | 1.3052 |
|
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| 1.2637 | 99.0 | 216810 | 1.3052 |
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| 1.2375 | 100.0 | 219000 | 1.3052 |
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### Framework versions
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- Transformers 4.39.3
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- Pytorch 2.1.2+cu121
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- Datasets 2.18.0
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- Tokenizers 0.15.2
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