rushikeshwalode/token_classification_NER

1---2library_name: transformers3license: apache-2.04base_model: distilbert/distilbert-base-uncased5tags:6- generated_from_trainer7metrics:8- precision9- recall10- f111- accuracy12model-index:13- name: token_classification_NER14  results: []15---16 17<!-- This model card has been generated automatically according to the information the Trainer had access to. You18should probably proofread and complete it, then remove this comment. -->19 20# token_classification_NER21 22This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on an unknown dataset.23It achieves the following results on the evaluation set:24- Loss: 0.293025- Precision: 0.553826- Recall: 0.357727- F1: 0.434728- Accuracy: 0.946029 30## Model description31 32More information needed33 34## Intended uses & limitations35 36More information needed37 38## Training and evaluation data39 40More information needed41 42## Training procedure43 44### Training hyperparameters45 46The following hyperparameters were used during training:47- learning_rate: 2e-0548- train_batch_size: 1649- eval_batch_size: 1650- seed: 4251- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments52- lr_scheduler_type: linear53- num_epochs: 554 55### Training results56 57| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |58|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|59| No log        | 1.0   | 213  | 0.2876          | 0.5724    | 0.2419 | 0.3401 | 0.9382   |60| No log        | 2.0   | 426  | 0.2626          | 0.5434    | 0.3133 | 0.3974 | 0.9431   |61| 0.1852        | 3.0   | 639  | 0.2846          | 0.5399    | 0.3262 | 0.4067 | 0.9446   |62| 0.1852        | 4.0   | 852  | 0.2875          | 0.5536    | 0.3494 | 0.4284 | 0.9458   |63| 0.0547        | 5.0   | 1065 | 0.2930          | 0.5538    | 0.3577 | 0.4347 | 0.9460   |64 65 66### Framework versions67 68- Transformers 4.53.369- Pytorch 2.11.0+cu12870- Datasets 4.0.071- Tokenizers 0.21.472