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roberta-Reflections-goodareas-sweeps-current

Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
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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: FacebookAI/roberta-large
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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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+ - precision
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+ - recall
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+ - f1
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+ model-index:
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+ - name: roberta-Reflections-goodareas-sweeps-current
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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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+ # roberta-Reflections-goodareas-sweeps-current
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+
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+ This model is a fine-tuned version of [FacebookAI/roberta-large](https://huggingface.co/FacebookAI/roberta-large) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.2162
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+ - Accuracy: 0.8704
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+ - Precision: 0.3861
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+ - Recall: 0.4699
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+ - F1: 0.4239
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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: 3.8996049006187325e-06
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+ - train_batch_size: 32
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+ - eval_batch_size: 16
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+ - seed: 42
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+ - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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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+ - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 20
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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 | Precision | Recall | F1 |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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+ | 0.4318 | 1.0 | 76 | 0.2203 | 0.8985 | 0.0 | 0.0 | 0.0 |
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+ | 0.3408 | 2.0 | 152 | 0.1981 | 0.8985 | 0.0 | 0.0 | 0.0 |
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+ | 0.278 | 3.0 | 228 | 0.1423 | 0.8973 | 0.4857 | 0.2048 | 0.2881 |
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+ | 0.2581 | 4.0 | 304 | 0.1200 | 0.8985 | 0.0 | 0.0 | 0.0 |
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+ | 0.2563 | 5.0 | 380 | 0.1929 | 0.8851 | 0.4154 | 0.3253 | 0.3649 |
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+ | 0.2431 | 6.0 | 456 | 0.1264 | 0.8985 | 0.5 | 0.0964 | 0.1616 |
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+ | 0.228 | 7.0 | 532 | 0.1889 | 0.8790 | 0.3947 | 0.3614 | 0.3774 |
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+ | 0.2204 | 8.0 | 608 | 0.1927 | 0.8875 | 0.4308 | 0.3373 | 0.3784 |
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+ | 0.2092 | 9.0 | 684 | 0.1467 | 0.8961 | 0.4773 | 0.2530 | 0.3307 |
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+ | 0.1985 | 10.0 | 760 | 0.1265 | 0.8961 | 0.4643 | 0.1566 | 0.2342 |
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+ | 0.1914 | 11.0 | 836 | 0.1567 | 0.8900 | 0.4146 | 0.2048 | 0.2742 |
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+ | 0.1715 | 12.0 | 912 | 0.1594 | 0.8875 | 0.4082 | 0.2410 | 0.3030 |
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+ | 0.1814 | 13.0 | 988 | 0.1718 | 0.8814 | 0.3906 | 0.3012 | 0.3401 |
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+ | 0.1507 | 14.0 | 1064 | 0.2037 | 0.8826 | 0.4330 | 0.5060 | 0.4667 |
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+ | 0.1448 | 15.0 | 1140 | 0.2165 | 0.8680 | 0.3853 | 0.5060 | 0.4375 |
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+ | 0.1329 | 16.0 | 1216 | 0.2395 | 0.8582 | 0.3659 | 0.5422 | 0.4369 |
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+ | 0.1334 | 17.0 | 1292 | 0.2133 | 0.8655 | 0.3689 | 0.4578 | 0.4086 |
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+ | 0.1298 | 18.0 | 1368 | 0.2145 | 0.8667 | 0.3673 | 0.4337 | 0.3978 |
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+ | 0.1226 | 19.0 | 1444 | 0.2129 | 0.8680 | 0.3684 | 0.4217 | 0.3933 |
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+ | 0.1215 | 20.0 | 1520 | 0.2162 | 0.8704 | 0.3861 | 0.4699 | 0.4239 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.48.3
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+ - Pytorch 2.5.1+cu124
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+ - Datasets 2.21.0
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+ - Tokenizers 0.21.0
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