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bert_baseline_language_task3_fold1

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  1. README.md +220 -0
  2. config.json +33 -0
  3. model.safetensors +3 -0
  4. runs/Aug22_10-22-58_0095ffe889f2/events.out.tfevents.1724322179.0095ffe889f2.25.0 +3 -0
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  6. runs/Aug22_11-07-47_0095ffe889f2/events.out.tfevents.1724324868.0095ffe889f2.25.2 +3 -0
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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: google-bert/bert-base-cased
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: bert_baseline_language_task3_fold0
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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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+ # bert_baseline_language_task3_fold0
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+
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+ This model is a fine-tuned version of [google-bert/bert-base-cased](https://huggingface.co/google-bert/bert-base-cased) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.3521
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+ - Qwk: 0.7259
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+ - Mse: 0.3521
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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: 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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+ - num_epochs: 5
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Qwk | Mse |
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+ |:-------------:|:------:|:----:|:---------------:|:------:|:------:|
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+ | No log | 0.0308 | 2 | 1.0742 | 0.0 | 1.0742 |
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+ | No log | 0.0615 | 4 | 0.8838 | 0.1229 | 0.8838 |
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+ | No log | 0.0923 | 6 | 0.8019 | 0.0086 | 0.8019 |
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+ | No log | 0.1231 | 8 | 0.7092 | 0.0 | 0.7092 |
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+ | No log | 0.1538 | 10 | 0.6954 | 0.0 | 0.6954 |
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+ | No log | 0.1846 | 12 | 0.6837 | 0.0 | 0.6837 |
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+ | No log | 0.2154 | 14 | 0.6200 | 0.0111 | 0.6200 |
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+ | No log | 0.2462 | 16 | 0.5494 | 0.0363 | 0.5494 |
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+ | No log | 0.2769 | 18 | 0.5037 | 0.1702 | 0.5037 |
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+ | No log | 0.3077 | 20 | 0.4594 | 0.2243 | 0.4594 |
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+ | No log | 0.3385 | 22 | 0.4261 | 0.3596 | 0.4261 |
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+ | No log | 0.3692 | 24 | 0.5071 | 0.6227 | 0.5071 |
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+ | No log | 0.4 | 26 | 0.5464 | 0.6449 | 0.5464 |
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+ | No log | 0.4308 | 28 | 0.4211 | 0.6562 | 0.4211 |
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+ | No log | 0.4615 | 30 | 0.3431 | 0.4949 | 0.3431 |
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+ | No log | 0.4923 | 32 | 0.3872 | 0.3807 | 0.3872 |
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+ | No log | 0.5231 | 34 | 0.3260 | 0.5141 | 0.3260 |
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+ | No log | 0.5538 | 36 | 0.3611 | 0.6467 | 0.3611 |
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+ | No log | 0.5846 | 38 | 0.4185 | 0.6712 | 0.4185 |
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+ | No log | 0.6154 | 40 | 0.3818 | 0.6453 | 0.3818 |
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+ | No log | 0.6462 | 42 | 0.3356 | 0.5296 | 0.3356 |
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+ | No log | 0.6769 | 44 | 0.3301 | 0.4987 | 0.3301 |
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+ | No log | 0.7077 | 46 | 0.3296 | 0.5764 | 0.3296 |
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+ | No log | 0.7385 | 48 | 0.3297 | 0.6715 | 0.3297 |
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+ | No log | 0.7692 | 50 | 0.3795 | 0.7089 | 0.3795 |
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+ | No log | 0.8 | 52 | 0.3864 | 0.7284 | 0.3864 |
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+ | No log | 0.8308 | 54 | 0.3003 | 0.6952 | 0.3003 |
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+ | No log | 0.8615 | 56 | 0.2974 | 0.6972 | 0.2974 |
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+ | No log | 0.8923 | 58 | 0.3138 | 0.7211 | 0.3138 |
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+ | No log | 0.9231 | 60 | 0.3076 | 0.7133 | 0.3076 |
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+ | No log | 0.9538 | 62 | 0.2889 | 0.6958 | 0.2889 |
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+ | No log | 0.9846 | 64 | 0.2828 | 0.6949 | 0.2828 |
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+ | No log | 1.0154 | 66 | 0.2738 | 0.6786 | 0.2738 |
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+ | No log | 1.0462 | 68 | 0.3007 | 0.7167 | 0.3007 |
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+ | No log | 1.0769 | 70 | 0.3616 | 0.7565 | 0.3616 |
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+ | No log | 1.1077 | 72 | 0.3960 | 0.7570 | 0.3960 |
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+ | No log | 1.1385 | 74 | 0.3368 | 0.7463 | 0.3368 |
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+ | No log | 1.1692 | 76 | 0.3325 | 0.7458 | 0.3325 |
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+ | No log | 1.2 | 78 | 0.3085 | 0.7053 | 0.3085 |
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+ | No log | 1.2308 | 80 | 0.3061 | 0.6892 | 0.3061 |
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+ | No log | 1.2615 | 82 | 0.3265 | 0.7044 | 0.3265 |
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+ | No log | 1.2923 | 84 | 0.3128 | 0.6883 | 0.3128 |
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+ | No log | 1.3231 | 86 | 0.2996 | 0.6739 | 0.2996 |
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+ | No log | 1.3538 | 88 | 0.3186 | 0.7086 | 0.3186 |
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+ | No log | 1.3846 | 90 | 0.3512 | 0.7429 | 0.3512 |
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+ | No log | 1.4154 | 92 | 0.3173 | 0.7394 | 0.3173 |
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+ | No log | 1.4462 | 94 | 0.2839 | 0.7018 | 0.2839 |
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+ | No log | 1.4769 | 96 | 0.2950 | 0.7105 | 0.2950 |
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+ | No log | 1.5077 | 98 | 0.2774 | 0.6970 | 0.2774 |
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+ | No log | 1.5385 | 100 | 0.2906 | 0.7139 | 0.2906 |
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+ | No log | 1.5692 | 102 | 0.3236 | 0.7346 | 0.3236 |
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+ | No log | 1.6 | 104 | 0.3657 | 0.7527 | 0.3657 |
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+ | No log | 1.6308 | 106 | 0.3119 | 0.7308 | 0.3119 |
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+ | No log | 1.6615 | 108 | 0.2950 | 0.7069 | 0.2950 |
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+ | No log | 1.6923 | 110 | 0.3509 | 0.7490 | 0.3509 |
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+ | No log | 1.7231 | 112 | 0.3472 | 0.7465 | 0.3472 |
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+ | No log | 1.7538 | 114 | 0.3468 | 0.7310 | 0.3468 |
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+ | No log | 1.7846 | 116 | 0.3669 | 0.7451 | 0.3669 |
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+ | No log | 1.8154 | 118 | 0.3531 | 0.7270 | 0.3531 |
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+ | No log | 1.8462 | 120 | 0.2999 | 0.6697 | 0.2999 |
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+ | No log | 1.8769 | 122 | 0.2856 | 0.6024 | 0.2856 |
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+ | No log | 1.9077 | 124 | 0.3008 | 0.6348 | 0.3008 |
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+ | No log | 1.9385 | 126 | 0.3631 | 0.7219 | 0.3631 |
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+ | No log | 1.9692 | 128 | 0.4466 | 0.7200 | 0.4466 |
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+ | No log | 2.0 | 130 | 0.4460 | 0.7224 | 0.4460 |
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+ | No log | 2.0308 | 132 | 0.3585 | 0.7346 | 0.3585 |
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+ | No log | 2.0615 | 134 | 0.2877 | 0.6459 | 0.2877 |
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+ | No log | 2.0923 | 136 | 0.2703 | 0.6297 | 0.2703 |
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+ | No log | 2.1231 | 138 | 0.2669 | 0.5792 | 0.2669 |
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+ | No log | 2.1538 | 140 | 0.2644 | 0.6690 | 0.2644 |
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+ | No log | 2.1846 | 142 | 0.3319 | 0.7553 | 0.3319 |
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+ | No log | 2.2154 | 144 | 0.4866 | 0.7578 | 0.4866 |
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+ | No log | 2.2462 | 146 | 0.5160 | 0.7452 | 0.5160 |
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+ | No log | 2.2769 | 148 | 0.4060 | 0.7715 | 0.4060 |
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+ | No log | 2.3077 | 150 | 0.2809 | 0.7028 | 0.2809 |
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+ | No log | 2.3385 | 152 | 0.2666 | 0.6490 | 0.2666 |
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+ | No log | 2.3692 | 154 | 0.2702 | 0.6734 | 0.2702 |
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+ | No log | 2.4 | 156 | 0.3248 | 0.7305 | 0.3248 |
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+ | No log | 2.4308 | 158 | 0.3987 | 0.7541 | 0.3987 |
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+ | No log | 2.4615 | 160 | 0.3924 | 0.7507 | 0.3924 |
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+ | No log | 2.4923 | 162 | 0.3604 | 0.7412 | 0.3604 |
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+ | No log | 2.5231 | 164 | 0.3018 | 0.7298 | 0.3018 |
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+ | No log | 2.5538 | 166 | 0.2686 | 0.6738 | 0.2686 |
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+ | No log | 2.5846 | 168 | 0.2798 | 0.6968 | 0.2798 |
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+ | No log | 2.6154 | 170 | 0.3557 | 0.7535 | 0.3557 |
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+ | No log | 2.6462 | 172 | 0.5145 | 0.7654 | 0.5145 |
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+ | No log | 2.6769 | 174 | 0.5778 | 0.7627 | 0.5778 |
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+ | No log | 2.7077 | 176 | 0.4912 | 0.7674 | 0.4912 |
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+ | No log | 2.7385 | 178 | 0.3387 | 0.7496 | 0.3387 |
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+ | No log | 2.7692 | 180 | 0.2719 | 0.6639 | 0.2719 |
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+ | No log | 2.8 | 182 | 0.2694 | 0.6642 | 0.2694 |
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+ | No log | 2.8308 | 184 | 0.2966 | 0.7089 | 0.2966 |
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+ | No log | 2.8615 | 186 | 0.3209 | 0.7242 | 0.3209 |
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+ | No log | 2.8923 | 188 | 0.3196 | 0.7123 | 0.3196 |
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+ | No log | 2.9231 | 190 | 0.3256 | 0.7156 | 0.3256 |
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+ | No log | 2.9538 | 192 | 0.3261 | 0.7146 | 0.3261 |
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+ | No log | 2.9846 | 194 | 0.3171 | 0.7089 | 0.3171 |
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+ | No log | 3.0154 | 196 | 0.3257 | 0.7122 | 0.3257 |
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+ | No log | 3.0462 | 198 | 0.3421 | 0.7065 | 0.3421 |
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+ | No log | 3.0769 | 200 | 0.3635 | 0.7217 | 0.3635 |
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+ | No log | 3.1077 | 202 | 0.3288 | 0.7127 | 0.3288 |
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+ | No log | 3.1385 | 204 | 0.3160 | 0.7000 | 0.3160 |
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+ | No log | 3.1692 | 206 | 0.3393 | 0.7142 | 0.3393 |
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+ | No log | 3.2 | 208 | 0.3507 | 0.7184 | 0.3507 |
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+ | No log | 3.2308 | 210 | 0.3357 | 0.7119 | 0.3357 |
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+ | No log | 3.2615 | 212 | 0.3227 | 0.7097 | 0.3227 |
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+ | No log | 3.2923 | 214 | 0.3567 | 0.7279 | 0.3567 |
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+ | No log | 3.3231 | 216 | 0.3730 | 0.7243 | 0.3730 |
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+ | No log | 3.3538 | 218 | 0.4105 | 0.7402 | 0.4105 |
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+ | No log | 3.3846 | 220 | 0.4438 | 0.7452 | 0.4438 |
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+ | No log | 3.4154 | 222 | 0.3973 | 0.7482 | 0.3973 |
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+ | No log | 3.4462 | 224 | 0.3496 | 0.7269 | 0.3496 |
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+ | No log | 3.4769 | 226 | 0.3634 | 0.7325 | 0.3634 |
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+ | No log | 3.5077 | 228 | 0.3641 | 0.7345 | 0.3641 |
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+ | No log | 3.5385 | 230 | 0.3980 | 0.7422 | 0.3980 |
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+ | No log | 3.5692 | 232 | 0.3894 | 0.7469 | 0.3894 |
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+ | No log | 3.6 | 234 | 0.3401 | 0.7209 | 0.3401 |
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+ | No log | 3.6308 | 236 | 0.2998 | 0.6977 | 0.2998 |
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+ | No log | 3.6615 | 238 | 0.3036 | 0.7083 | 0.3036 |
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+ | No log | 3.6923 | 240 | 0.3472 | 0.7299 | 0.3472 |
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+ | No log | 3.7231 | 242 | 0.4207 | 0.7555 | 0.4207 |
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+ | No log | 3.7538 | 244 | 0.4344 | 0.7661 | 0.4344 |
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+ | No log | 3.7846 | 246 | 0.3979 | 0.7539 | 0.3979 |
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+ | No log | 3.8154 | 248 | 0.3403 | 0.7074 | 0.3403 |
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+ | No log | 3.8462 | 250 | 0.3189 | 0.6990 | 0.3189 |
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+ | No log | 3.8769 | 252 | 0.3197 | 0.6990 | 0.3197 |
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+ | No log | 3.9077 | 254 | 0.3434 | 0.7109 | 0.3434 |
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+ | No log | 3.9385 | 256 | 0.3713 | 0.7356 | 0.3713 |
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+ | No log | 3.9692 | 258 | 0.4017 | 0.7487 | 0.4017 |
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+ | No log | 4.0 | 260 | 0.4081 | 0.7449 | 0.4081 |
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+ | No log | 4.0308 | 262 | 0.4139 | 0.7494 | 0.4139 |
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+ | No log | 4.0615 | 264 | 0.3796 | 0.7418 | 0.3796 |
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+ | No log | 4.0923 | 266 | 0.3484 | 0.7227 | 0.3484 |
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+ | No log | 4.1231 | 268 | 0.3313 | 0.7029 | 0.3313 |
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+ | No log | 4.1538 | 270 | 0.3159 | 0.7044 | 0.3159 |
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+ | No log | 4.1846 | 272 | 0.3217 | 0.7087 | 0.3217 |
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+ | No log | 4.2154 | 274 | 0.3284 | 0.7084 | 0.3284 |
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+ | No log | 4.2462 | 276 | 0.3511 | 0.7292 | 0.3511 |
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+ | No log | 4.2769 | 278 | 0.3811 | 0.7486 | 0.3811 |
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+ | No log | 4.3077 | 280 | 0.3992 | 0.7491 | 0.3992 |
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+ | No log | 4.3385 | 282 | 0.3909 | 0.7470 | 0.3909 |
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+ | No log | 4.3692 | 284 | 0.3704 | 0.7361 | 0.3704 |
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+ | No log | 4.4 | 286 | 0.3576 | 0.7266 | 0.3576 |
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+ | No log | 4.4308 | 288 | 0.3437 | 0.7170 | 0.3437 |
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+ | No log | 4.4615 | 290 | 0.3401 | 0.7157 | 0.3401 |
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+ | No log | 4.4923 | 292 | 0.3461 | 0.7221 | 0.3461 |
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+ | No log | 4.5231 | 294 | 0.3697 | 0.7311 | 0.3697 |
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+ | No log | 4.5538 | 296 | 0.4014 | 0.7583 | 0.4014 |
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+ | No log | 4.5846 | 298 | 0.4056 | 0.7603 | 0.4056 |
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+ | No log | 4.6154 | 300 | 0.3995 | 0.7583 | 0.3995 |
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+ | No log | 4.6462 | 302 | 0.3932 | 0.7532 | 0.3932 |
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+ | No log | 4.6769 | 304 | 0.3791 | 0.7385 | 0.3791 |
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+ | No log | 4.7077 | 306 | 0.3658 | 0.7392 | 0.3658 |
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+ | No log | 4.7385 | 308 | 0.3571 | 0.7321 | 0.3571 |
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+ | No log | 4.7692 | 310 | 0.3445 | 0.7166 | 0.3445 |
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+ | No log | 4.8 | 312 | 0.3390 | 0.7175 | 0.3390 |
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+ | No log | 4.8308 | 314 | 0.3394 | 0.7177 | 0.3394 |
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+ | No log | 4.8615 | 316 | 0.3438 | 0.7157 | 0.3438 |
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+ | No log | 4.8923 | 318 | 0.3471 | 0.7159 | 0.3471 |
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+ | No log | 4.9231 | 320 | 0.3502 | 0.7209 | 0.3502 |
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+ | No log | 4.9538 | 322 | 0.3516 | 0.7259 | 0.3516 |
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+ | No log | 4.9846 | 324 | 0.3521 | 0.7259 | 0.3521 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.42.3
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+ - Pytorch 2.1.2
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+ - Datasets 2.20.0
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+ - Tokenizers 0.19.1
config.json ADDED
@@ -0,0 +1,33 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ {
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+ "_name_or_path": "google-bert/bert-base-cased",
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+ "architectures": [
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+ "BertForSequenceClassification"
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+ ],
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+ "attention_probs_dropout_prob": 0.1,
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+ "classifier_dropout": null,
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+ "gradient_checkpointing": false,
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+ "hidden_act": "gelu",
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+ "hidden_dropout_prob": 0.1,
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+ "hidden_size": 768,
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+ "id2label": {
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+ "0": "LABEL_0"
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+ },
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+ "initializer_range": 0.02,
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+ "intermediate_size": 3072,
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+ "label2id": {
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+ "LABEL_0": 0
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+ },
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+ "layer_norm_eps": 1e-12,
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+ "max_position_embeddings": 512,
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+ "model_type": "bert",
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+ "num_attention_heads": 12,
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+ "num_hidden_layers": 12,
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+ "pad_token_id": 0,
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+ "position_embedding_type": "absolute",
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+ "problem_type": "regression",
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.42.3",
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+ "type_vocab_size": 2,
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+ "use_cache": true,
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+ "vocab_size": 28996
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+ }
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