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idah4
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qa_kor_market

Text2Text Generation
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bart
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  1. README.md +175 -0
  2. generation_config.json +9 -0
  3. model.safetensors +1 -1
  4. runs/Apr16_00-01-30_a5ac0e95e35a/events.out.tfevents.1713225695.a5ac0e95e35a.353.0 +2 -2
README.md ADDED
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+ ---
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+ license: mit
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+ base_model: hyunwoongko/kobart
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: qa_kor_market
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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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+ # qa_kor_market
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+
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+ This model is a fine-tuned version of [hyunwoongko/kobart](https://huggingface.co/hyunwoongko/kobart) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.7618
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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: 16
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+ - eval_batch_size: 16
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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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+ - lr_scheduler_warmup_steps: 400
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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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+ | No log | 0.03 | 100 | 3.4839 |
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+ | No log | 0.05 | 200 | 1.4909 |
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+ | No log | 0.08 | 300 | 1.2606 |
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+ | No log | 0.1 | 400 | 1.1675 |
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+ | 3.0259 | 0.13 | 500 | 1.1008 |
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+ | 3.0259 | 0.15 | 600 | 1.0580 |
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+ | 3.0259 | 0.18 | 700 | 1.0222 |
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+ | 3.0259 | 0.2 | 800 | 0.9938 |
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+ | 3.0259 | 0.23 | 900 | 0.9707 |
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+ | 1.0853 | 0.25 | 1000 | 0.9571 |
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+ | 1.0853 | 0.28 | 1100 | 0.9370 |
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+ | 1.0853 | 0.3 | 1200 | 0.9293 |
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+ | 1.0853 | 0.33 | 1300 | 0.9146 |
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+ | 1.0853 | 0.35 | 1400 | 0.9065 |
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+ | 0.992 | 0.38 | 1500 | 0.8997 |
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+ | 0.992 | 0.41 | 1600 | 0.8930 |
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+ | 0.992 | 0.43 | 1700 | 0.8834 |
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+ | 0.992 | 0.46 | 1800 | 0.8788 |
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+ | 0.992 | 0.48 | 1900 | 0.8714 |
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+ | 0.9418 | 0.51 | 2000 | 0.8706 |
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+ | 0.9418 | 0.53 | 2100 | 0.8676 |
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+ | 0.9418 | 0.56 | 2200 | 0.8619 |
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+ | 0.9418 | 0.58 | 2300 | 0.8548 |
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+ | 0.9418 | 0.61 | 2400 | 0.8514 |
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+ | 0.9222 | 0.63 | 2500 | 0.8511 |
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+ | 0.9222 | 0.66 | 2600 | 0.8483 |
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+ | 0.9222 | 0.68 | 2700 | 0.8425 |
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+ | 0.9222 | 0.71 | 2800 | 0.8396 |
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+ | 0.9222 | 0.74 | 2900 | 0.8384 |
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+ | 0.8981 | 0.76 | 3000 | 0.8360 |
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+ | 0.8981 | 0.79 | 3100 | 0.8295 |
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+ | 0.8981 | 0.81 | 3200 | 0.8290 |
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+ | 0.8981 | 0.84 | 3300 | 0.8273 |
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+ | 0.8981 | 0.86 | 3400 | 0.8221 |
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+ | 0.874 | 0.89 | 3500 | 0.8228 |
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+ | 0.874 | 0.91 | 3600 | 0.8213 |
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+ | 0.874 | 0.94 | 3700 | 0.8183 |
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+ | 0.874 | 0.96 | 3800 | 0.8163 |
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+ | 0.874 | 0.99 | 3900 | 0.8178 |
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+ | 0.8575 | 1.01 | 4000 | 0.8143 |
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+ | 0.8575 | 1.04 | 4100 | 0.8118 |
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+ | 0.8575 | 1.06 | 4200 | 0.8094 |
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+ | 0.8575 | 1.09 | 4300 | 0.8092 |
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+ | 0.8575 | 1.12 | 4400 | 0.8085 |
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+ | 0.8374 | 1.14 | 4500 | 0.8048 |
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+ | 0.8374 | 1.17 | 4600 | 0.8041 |
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+ | 0.8374 | 1.19 | 4700 | 0.8018 |
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+ | 0.8374 | 1.22 | 4800 | 0.8007 |
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+ | 0.8374 | 1.24 | 4900 | 0.7988 |
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+ | 0.8282 | 1.27 | 5000 | 0.7980 |
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+ | 0.8282 | 1.29 | 5100 | 0.7968 |
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+ | 0.8282 | 1.32 | 5200 | 0.7974 |
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+ | 0.8282 | 1.34 | 5300 | 0.7949 |
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+ | 0.8282 | 1.37 | 5400 | 0.7919 |
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+ | 0.8149 | 1.39 | 5500 | 0.7931 |
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+ | 0.8149 | 1.42 | 5600 | 0.7900 |
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+ | 0.8149 | 1.44 | 5700 | 0.7887 |
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+ | 0.8149 | 1.47 | 5800 | 0.7875 |
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+ | 0.8149 | 1.5 | 5900 | 0.7883 |
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+ | 0.8098 | 1.52 | 6000 | 0.7886 |
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+ | 0.8098 | 1.55 | 6100 | 0.7860 |
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+ | 0.8098 | 1.57 | 6200 | 0.7873 |
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+ | 0.8098 | 1.6 | 6300 | 0.7822 |
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+ | 0.8098 | 1.62 | 6400 | 0.7841 |
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+ | 0.8306 | 1.65 | 6500 | 0.7828 |
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+ | 0.8306 | 1.67 | 6600 | 0.7817 |
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+ | 0.8306 | 1.7 | 6700 | 0.7812 |
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+ | 0.8306 | 1.72 | 6800 | 0.7814 |
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+ | 0.8306 | 1.75 | 6900 | 0.7799 |
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+ | 0.7974 | 1.77 | 7000 | 0.7774 |
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+ | 0.7974 | 1.8 | 7100 | 0.7795 |
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+ | 0.7974 | 1.83 | 7200 | 0.7782 |
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+ | 0.7974 | 1.85 | 7300 | 0.7786 |
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+ | 0.7974 | 1.88 | 7400 | 0.7773 |
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+ | 0.7945 | 1.9 | 7500 | 0.7749 |
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+ | 0.7945 | 1.93 | 7600 | 0.7737 |
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+ | 0.7945 | 1.95 | 7700 | 0.7743 |
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+ | 0.7945 | 1.98 | 7800 | 0.7742 |
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+ | 0.7945 | 2.0 | 7900 | 0.7732 |
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+ | 0.8005 | 2.03 | 8000 | 0.7758 |
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+ | 0.8005 | 2.05 | 8100 | 0.7726 |
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+ | 0.8005 | 2.08 | 8200 | 0.7716 |
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+ | 0.8005 | 2.1 | 8300 | 0.7742 |
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+ | 0.8005 | 2.13 | 8400 | 0.7720 |
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+ | 0.7788 | 2.15 | 8500 | 0.7706 |
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+ | 0.7788 | 2.18 | 8600 | 0.7701 |
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+ | 0.7788 | 2.21 | 8700 | 0.7702 |
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+ | 0.7788 | 2.23 | 8800 | 0.7676 |
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+ | 0.7788 | 2.26 | 8900 | 0.7699 |
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+ | 0.7685 | 2.28 | 9000 | 0.7689 |
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+ | 0.7685 | 2.31 | 9100 | 0.7677 |
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+ | 0.7685 | 2.33 | 9200 | 0.7686 |
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+ | 0.7685 | 2.36 | 9300 | 0.7671 |
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+ | 0.7685 | 2.38 | 9400 | 0.7668 |
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+ | 0.7814 | 2.41 | 9500 | 0.7670 |
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+ | 0.7814 | 2.43 | 9600 | 0.7669 |
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+ | 0.7814 | 2.46 | 9700 | 0.7661 |
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+ | 0.7814 | 2.48 | 9800 | 0.7653 |
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+ | 0.7814 | 2.51 | 9900 | 0.7663 |
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+ | 0.7824 | 2.53 | 10000 | 0.7655 |
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+ | 0.7824 | 2.56 | 10100 | 0.7654 |
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+ | 0.7824 | 2.59 | 10200 | 0.7653 |
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+ | 0.7824 | 2.61 | 10300 | 0.7652 |
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+ | 0.7824 | 2.64 | 10400 | 0.7640 |
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+ | 0.7798 | 2.66 | 10500 | 0.7647 |
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+ | 0.7798 | 2.69 | 10600 | 0.7637 |
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+ | 0.7798 | 2.71 | 10700 | 0.7636 |
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+ | 0.7798 | 2.74 | 10800 | 0.7629 |
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+ | 0.7798 | 2.76 | 10900 | 0.7629 |
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+ | 0.7619 | 2.79 | 11000 | 0.7629 |
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+ | 0.7619 | 2.81 | 11100 | 0.7624 |
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+ | 0.7619 | 2.84 | 11200 | 0.7621 |
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+ | 0.7619 | 2.86 | 11300 | 0.7621 |
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+ | 0.7619 | 2.89 | 11400 | 0.7623 |
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+ | 0.7723 | 2.92 | 11500 | 0.7621 |
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+ | 0.7723 | 2.94 | 11600 | 0.7619 |
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+ | 0.7723 | 2.97 | 11700 | 0.7619 |
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+ | 0.7723 | 2.99 | 11800 | 0.7618 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.38.2
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+ - Pytorch 2.2.1+cu121
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+ - Datasets 2.18.0
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+ - Tokenizers 0.15.2
generation_config.json ADDED
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+ {
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+ "_from_model_config": true,
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+ "bos_token_id": 1,
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+ "decoder_start_token_id": 1,
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+ "eos_token_id": 1,
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+ "forced_eos_token_id": 1,
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+ "pad_token_id": 3,
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+ "transformers_version": "4.38.2"
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+ }
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