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+ ---
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: testc8-2
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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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+ # testc8-2
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+
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+ This model is a fine-tuned version of [shafin/chemical-bert-uncased-finetuned-cust-c2](https://huggingface.co/shafin/chemical-bert-uncased-finetuned-cust-c2) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.2346
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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: 64
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+ - eval_batch_size: 64
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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: 30
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+ - mixed_precision_training: Native AMP
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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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+ | 0.6173 | 1.0 | 16 | 0.3874 |
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+ | 0.5383 | 2.0 | 32 | 0.3227 |
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+ | 0.4756 | 3.0 | 48 | 0.3142 |
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+ | 0.4399 | 4.0 | 64 | 0.3404 |
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+ | 0.4462 | 5.0 | 80 | 0.3112 |
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+ | 0.4187 | 6.0 | 96 | 0.3185 |
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+ | 0.4023 | 7.0 | 112 | 0.2628 |
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+ | 0.3712 | 8.0 | 128 | 0.2807 |
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+ | 0.3922 | 9.0 | 144 | 0.2516 |
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+ | 0.3483 | 10.0 | 160 | 0.1995 |
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+ | 0.3417 | 11.0 | 176 | 0.2452 |
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+ | 0.3585 | 12.0 | 192 | 0.2236 |
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+ | 0.3413 | 13.0 | 208 | 0.2031 |
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+ | 0.3452 | 14.0 | 224 | 0.2238 |
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+ | 0.317 | 15.0 | 240 | 0.2229 |
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+ | 0.3161 | 16.0 | 256 | 0.2591 |
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+ | 0.3338 | 17.0 | 272 | 0.2599 |
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+ | 0.2949 | 18.0 | 288 | 0.2618 |
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+ | 0.3035 | 19.0 | 304 | 0.2436 |
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+ | 0.3108 | 20.0 | 320 | 0.2015 |
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+ | 0.289 | 21.0 | 336 | 0.2329 |
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+ | 0.3144 | 22.0 | 352 | 0.1940 |
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+ | 0.2606 | 23.0 | 368 | 0.2334 |
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+ | 0.2842 | 24.0 | 384 | 0.1996 |
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+ | 0.2892 | 25.0 | 400 | 0.2330 |
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+ | 0.2612 | 26.0 | 416 | 0.2163 |
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+ | 0.2669 | 27.0 | 432 | 0.2053 |
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+ | 0.3147 | 28.0 | 448 | 0.1555 |
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+ | 0.286 | 29.0 | 464 | 0.1983 |
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+ | 0.2857 | 30.0 | 480 | 0.2346 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.24.0
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+ - Pytorch 1.12.1+cu113
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+ - Datasets 2.7.1
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+ - Tokenizers 0.13.2