End of training

README.md

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+---
+license: apache-2.0
+base_model: google/muril-base-cased
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: urdu-muril-ner
+ results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# urdu-muril-ner
+
+This model is a fine-tuned version of [google/muril-base-cased](https://huggingface.co/google/muril-base-cased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1489
+- Precision: 0.7802
+- Recall: 0.8229
+- F1: 0.8009
+- Accuracy: 0.9570
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 2e-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
+|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.3946 | 1.0 | 2272 | 0.3188 | 0.7387 | 0.6442 | 0.6882 | 0.9350 |
+| 0.2026 | 2.0 | 4544 | 0.1960 | 0.7728 | 0.7797 | 0.7762 | 0.9535 |
+| 0.141 | 3.0 | 6816 | 0.1554 | 0.7735 | 0.8139 | 0.7932 | 0.9557 |
+| 0.1038 | 4.0 | 9088 | 0.1474 | 0.7836 | 0.8163 | 0.7996 | 0.9568 |
+| 0.0889 | 5.0 | 11360 | 0.1489 | 0.7802 | 0.8229 | 0.8009 | 0.9570 |
+
+
+### Framework versions
+
+- Transformers 4.34.0
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.5
+- Tokenizers 0.14.1

added_tokens.json

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+ "[MASK]": 103,
+ "[PAD]": 0,
+ "[SEP]": 105,
+ "[UNK]": 100
+}

config.json

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+{
+ "_name_or_path": "google/muril-base-cased",
+ "architectures": [
+ "BertForTokenClassification"
+ ],
+ "attention_probs_dropout_prob": 0.1,
+ "classifier_dropout": null,
+ "embedding_size": 768,
+ "hidden_act": "gelu",
+ "hidden_dropout_prob": 0.1,
+ "hidden_size": 768,
+ "id2label": {
+ "0": "TIME",
+ "1": "PERSON",
+ "2": "ORGANIZATION",
+ "3": "O",
+ "4": "NUMBER",
+ "5": "LOCATION",
+ "6": "DESIGNATION",
+ "7": "DATE"
+ },
+ "initializer_range": 0.02,
+ "intermediate_size": 3072,
+ "label2id": {
+ "DATE": 7,
+ "DESIGNATION": 6,
+ "LOCATION": 5,
+ "NUMBER": 4,
+ "O": 3,
+ "ORGANIZATION": 2,
+ "PERSON": 1,
+ "TIME": 0
+ },
+ "layer_norm_eps": 1e-12,
+ "max_position_embeddings": 512,
+ "model_type": "bert",
+ "num_attention_heads": 12,
+ "num_hidden_layers": 12,
+ "pad_token_id": 0,
+ "position_embedding_type": "absolute",
+ "torch_dtype": "float32",
+ "transformers_version": "4.34.0",
+ "type_vocab_size": 2,
+ "use_cache": true,
+ "vocab_size": 197285
+}

pytorch_model.bin

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special_tokens_map.json

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+ "cls_token": "[CLS]",
+ "mask_token": "[MASK]",
+ "pad_token": "[PAD]",
+ "sep_token": "[SEP]",
+ "unk_token": "[UNK]"
+}

tokenizer_config.json

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+{
+ "added_tokens_decoder": {
+ "0": {
+ "content": "[PAD]",
+ "lstrip": false,
+ "normalized": false,
+ "rstrip": false,
+ "single_word": false,
+ "special": true
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+ "special": true
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+ "lstrip": false,
+ "normalized": false,
+ "rstrip": false,
+ "single_word": false,
+ "special": true
+ }
+ },
+ "additional_special_tokens": [],
+ "clean_up_tokenization_spaces": true,
+ "cls_token": "[CLS]",
+ "do_basic_tokenize": true,
+ "do_lower_case": false,
+ "lowercase": false,
+ "mask_token": "[MASK]",
+ "model_max_length": 512,
+ "never_split": null,
+ "pad_token": "[PAD]",
+ "sep_token": "[SEP]",
+ "strip_accents": false,
+ "tokenize_chinese_chars": true,
+ "tokenizer_class": "BertTokenizer",
+ "unk_token": "[UNK]"
+}

training_args.bin

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