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mr-kush/sambodhan-department-classification-model

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  1. README.md +79 -0
  2. config.json +40 -0
  3. model.safetensors +3 -0
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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/xlm-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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+ - f1
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+ - precision
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+ - recall
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+ model-index:
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+ - name: trainer_output
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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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+ # trainer_output
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+
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+ This model is a fine-tuned version of [FacebookAI/xlm-roberta-base](https://huggingface.co/FacebookAI/xlm-roberta-base) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 2.0023
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+ - Accuracy: 0.8598
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+ - F1: 0.8668
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+ - Precision: 0.8770
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+ - Recall: 0.8598
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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: 32
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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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+ - num_epochs: 3
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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 | Accuracy | F1 | Precision | Recall |
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+ |:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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+ | No log | 0.2439 | 20 | 1.6724 | 0.8537 | 0.8597 | 0.8721 | 0.8537 |
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+ | No log | 0.4878 | 40 | 2.1847 | 0.8598 | 0.8618 | 0.8640 | 0.8598 |
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+ | 0.3126 | 0.7317 | 60 | 2.0168 | 0.8598 | 0.8630 | 0.8673 | 0.8598 |
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+ | 0.3126 | 0.9756 | 80 | 2.4119 | 0.8780 | 0.8804 | 0.8904 | 0.8780 |
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+ | 0.2521 | 1.2195 | 100 | 2.2020 | 0.8902 | 0.8884 | 0.8899 | 0.8902 |
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+ | 0.2521 | 1.4634 | 120 | 2.2252 | 0.8902 | 0.8893 | 0.8908 | 0.8902 |
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+ | 0.2521 | 1.7073 | 140 | 1.9534 | 0.8476 | 0.8579 | 0.8738 | 0.8476 |
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+ | 0.2102 | 1.9512 | 160 | 2.0566 | 0.8963 | 0.8952 | 0.8948 | 0.8963 |
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+ | 0.2102 | 2.1951 | 180 | 2.1647 | 0.8659 | 0.8714 | 0.8799 | 0.8659 |
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+ | 0.0475 | 2.4390 | 200 | 2.2178 | 0.8659 | 0.8713 | 0.8795 | 0.8659 |
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+ | 0.0475 | 2.6829 | 220 | 2.2616 | 0.8659 | 0.8713 | 0.8795 | 0.8659 |
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+ | 0.0475 | 2.9268 | 240 | 2.2667 | 0.8659 | 0.8713 | 0.8795 | 0.8659 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.56.2
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+ - Pytorch 2.8.0+cu126
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+ - Datasets 4.0.0
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+ - Tokenizers 0.22.1
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+ {
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+ "architectures": [
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+ "XLMRobertaForSequenceClassification"
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+ ],
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+ "attention_probs_dropout_prob": 0.1,
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+ "bos_token_id": 0,
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+ "classifier_dropout": null,
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+ "dtype": "float32",
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+ "eos_token_id": 2,
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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": "Municipal Governance & Community Services",
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+ "1": "Education, Health & Social Welfare",
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+ "2": "Infrastructure, Utilities & Natural Resources",
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+ "3": "Security & Law Enforcement"
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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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+ "Education, Health & Social Welfare": 1,
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+ "Infrastructure, Utilities & Natural Resources": 2,
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+ "Municipal Governance & Community Services": 0,
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+ "Security & Law Enforcement": 3
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+ },
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+ "layer_norm_eps": 1e-05,
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+ "max_position_embeddings": 514,
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+ "model_type": "xlm-roberta",
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+ "num_attention_heads": 12,
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+ "num_hidden_layers": 12,
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+ "output_past": true,
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+ "pad_token_id": 1,
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+ "position_embedding_type": "absolute",
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+ "problem_type": "single_label_classification",
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+ "transformers_version": "4.56.2",
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+ "type_vocab_size": 1,
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+ "use_cache": true,
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+ "vocab_size": 250002
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+ }
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