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dipteshkanojia
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hing-roberta-NCM-run-2

Text Classification
Transformers
PyTorch
xlm-roberta
Generated from Trainer
Inference Endpoints
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+ ---
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+ license: cc-by-4.0
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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: hing-roberta-NCM-run-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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+ # hing-roberta-NCM-run-2
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+
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+ This model is a fine-tuned version of [l3cube-pune/hing-roberta](https://huggingface.co/l3cube-pune/hing-roberta) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 3.3647
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+ - Accuracy: 0.6483
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+ - Precision: 0.6369
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+ - Recall: 0.6325
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+ - F1: 0.6341
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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: 8
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+ - eval_batch_size: 8
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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: 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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+ | 0.8973 | 1.0 | 927 | 0.8166 | 0.6483 | 0.6545 | 0.6576 | 0.6460 |
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+ | 0.6827 | 2.0 | 1854 | 0.9071 | 0.6526 | 0.6444 | 0.6261 | 0.6299 |
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+ | 0.4672 | 3.0 | 2781 | 1.1600 | 0.6764 | 0.6657 | 0.6634 | 0.6643 |
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+ | 0.3388 | 4.0 | 3708 | 1.7426 | 0.6548 | 0.6406 | 0.6442 | 0.6418 |
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+ | 0.2786 | 5.0 | 4635 | 1.9385 | 0.6505 | 0.6484 | 0.6437 | 0.6434 |
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+ | 0.1794 | 6.0 | 5562 | 2.3158 | 0.6472 | 0.6564 | 0.6365 | 0.6388 |
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+ | 0.12 | 7.0 | 6489 | 2.6961 | 0.6591 | 0.6458 | 0.6531 | 0.6466 |
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+ | 0.1298 | 8.0 | 7416 | 2.7196 | 0.6505 | 0.6523 | 0.6307 | 0.6342 |
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+ | 0.0941 | 9.0 | 8343 | 2.5853 | 0.6548 | 0.6406 | 0.6426 | 0.6415 |
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+ | 0.0696 | 10.0 | 9270 | 2.8386 | 0.6613 | 0.6616 | 0.6314 | 0.6348 |
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+ | 0.0722 | 11.0 | 10197 | 2.9658 | 0.6537 | 0.6356 | 0.6356 | 0.6355 |
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+ | 0.0509 | 12.0 | 11124 | 3.3286 | 0.6429 | 0.6262 | 0.6192 | 0.6214 |
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+ | 0.0444 | 13.0 | 12051 | 3.1654 | 0.6483 | 0.6347 | 0.6302 | 0.6319 |
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+ | 0.0341 | 14.0 | 12978 | 2.9509 | 0.6537 | 0.6430 | 0.6394 | 0.6401 |
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+ | 0.0345 | 15.0 | 13905 | 3.3416 | 0.6656 | 0.6514 | 0.6488 | 0.6499 |
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+ | 0.0303 | 16.0 | 14832 | 3.3874 | 0.6419 | 0.6267 | 0.6339 | 0.6272 |
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+ | 0.0245 | 17.0 | 15759 | 3.2854 | 0.6570 | 0.6428 | 0.6420 | 0.6421 |
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+ | 0.0174 | 18.0 | 16686 | 3.2863 | 0.6602 | 0.6569 | 0.6427 | 0.6465 |
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+ | 0.0136 | 19.0 | 17613 | 3.3674 | 0.6494 | 0.6361 | 0.6341 | 0.6349 |
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+ | 0.0111 | 20.0 | 18540 | 3.3647 | 0.6483 | 0.6369 | 0.6325 | 0.6341 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.20.1
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+ - Pytorch 1.10.1+cu111
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+ - Datasets 2.3.2
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+ - Tokenizers 0.12.1