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SST-2-FULL_FT-seed10

Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
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README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: mit
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+ base_model: roberta-base
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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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+ model-index:
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+ - name: SST-2-FULL_FT-seed10
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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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+ # SST-2-FULL_FT-seed10
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+
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+ This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.3049
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+ - Accuracy: 0.9415
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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: 3e-05
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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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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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 | Accuracy |
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+ |:-------------:|:------:|:-----:|:---------------:|:--------:|
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+ | 0.4039 | 0.0950 | 200 | 0.2241 | 0.9140 |
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+ | 0.2971 | 0.1900 | 400 | 0.2148 | 0.9163 |
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+ | 0.2716 | 0.2850 | 600 | 0.2114 | 0.9266 |
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+ | 0.2327 | 0.3800 | 800 | 0.2143 | 0.9232 |
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+ | 0.2222 | 0.4751 | 1000 | 0.3102 | 0.9048 |
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+ | 0.2166 | 0.5701 | 1200 | 0.2533 | 0.9220 |
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+ | 0.2112 | 0.6651 | 1400 | 0.2210 | 0.9312 |
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+ | 0.199 | 0.7601 | 1600 | 0.2412 | 0.9255 |
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+ | 0.205 | 0.8551 | 1800 | 0.2204 | 0.9289 |
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+ | 0.188 | 0.9501 | 2000 | 0.2112 | 0.9346 |
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+ | 0.1783 | 1.0451 | 2200 | 0.2042 | 0.9369 |
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+ | 0.1502 | 1.1401 | 2400 | 0.1916 | 0.9392 |
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+ | 0.155 | 1.2352 | 2600 | 0.2369 | 0.9335 |
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+ | 0.1417 | 1.3302 | 2800 | 0.2446 | 0.9300 |
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+ | 0.1452 | 1.4252 | 3000 | 0.2524 | 0.9255 |
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+ | 0.1454 | 1.5202 | 3200 | 0.2622 | 0.9255 |
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+ | 0.1517 | 1.6152 | 3400 | 0.1906 | 0.9255 |
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+ | 0.1396 | 1.7102 | 3600 | 0.2471 | 0.9209 |
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+ | 0.1422 | 1.8052 | 3800 | 0.2245 | 0.9323 |
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+ | 0.1522 | 1.9002 | 4000 | 0.2231 | 0.9358 |
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+ | 0.1438 | 1.9952 | 4200 | 0.2113 | 0.9381 |
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+ | 0.1173 | 2.0903 | 4400 | 0.2444 | 0.9346 |
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+ | 0.1116 | 2.1853 | 4600 | 0.2508 | 0.9335 |
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+ | 0.1085 | 2.2803 | 4800 | 0.3127 | 0.9266 |
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+ | 0.1123 | 2.3753 | 5000 | 0.2474 | 0.9243 |
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+ | 0.1067 | 2.4703 | 5200 | 0.2621 | 0.9300 |
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+ | 0.1018 | 2.5653 | 5400 | 0.2460 | 0.9358 |
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+ | 0.1232 | 2.6603 | 5600 | 0.2445 | 0.9358 |
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+ | 0.097 | 2.7553 | 5800 | 0.2641 | 0.9289 |
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+ | 0.1085 | 2.8504 | 6000 | 0.2546 | 0.9300 |
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+ | 0.0959 | 2.9454 | 6200 | 0.2663 | 0.9358 |
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+ | 0.0961 | 3.0404 | 6400 | 0.2741 | 0.9358 |
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+ | 0.0818 | 3.1354 | 6600 | 0.2428 | 0.9369 |
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+ | 0.0791 | 3.2304 | 6800 | 0.2717 | 0.9346 |
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+ | 0.0838 | 3.3254 | 7000 | 0.2503 | 0.9358 |
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+ | 0.0815 | 3.4204 | 7200 | 0.2384 | 0.9392 |
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+ | 0.0763 | 3.5154 | 7400 | 0.3029 | 0.9312 |
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+ | 0.0776 | 3.6105 | 7600 | 0.2866 | 0.9335 |
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+ | 0.0853 | 3.7055 | 7800 | 0.2533 | 0.9369 |
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+ | 0.088 | 3.8005 | 8000 | 0.2809 | 0.9335 |
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+ | 0.0775 | 3.8955 | 8200 | 0.2812 | 0.9369 |
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+ | 0.081 | 3.9905 | 8400 | 0.2522 | 0.9346 |
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+ | 0.0581 | 4.0855 | 8600 | 0.2981 | 0.9323 |
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+ | 0.0484 | 4.1805 | 8800 | 0.3132 | 0.9369 |
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+ | 0.0649 | 4.2755 | 9000 | 0.3049 | 0.9415 |
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+ | 0.0644 | 4.3705 | 9200 | 0.2986 | 0.9358 |
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+ | 0.0607 | 4.4656 | 9400 | 0.2718 | 0.9404 |
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+ | 0.0533 | 4.5606 | 9600 | 0.2927 | 0.9392 |
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+ | 0.0641 | 4.6556 | 9800 | 0.2875 | 0.9381 |
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+ | 0.0605 | 4.7506 | 10000 | 0.2811 | 0.9381 |
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+ | 0.0611 | 4.8456 | 10200 | 0.2845 | 0.9358 |
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+ | 0.0575 | 4.9406 | 10400 | 0.2866 | 0.9381 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.54.1
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+ - Pytorch 2.5.1+cu121
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+ - Datasets 4.0.0
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+ - Tokenizers 0.21.4
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