End of training

README.md

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+---
+language:
+- mn
+base_model: bayartsogt/mongolian-roberta-base
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: roberta-base-ner-test
+  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. -->
+
+# roberta-base-ner-test
+
+This model is a fine-tuned version of [bayartsogt/mongolian-roberta-base](https://huggingface.co/bayartsogt/mongolian-roberta-base) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1051
+- Precision: 0.9154
+- Recall: 0.9295
+- F1: 0.9224
+- Accuracy: 0.9778
+
+## 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: 128
+- eval_batch_size: 64
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.4118        | 1.0   | 60   | 0.1230          | 0.7683    | 0.8344 | 0.8000 | 0.9584   |
+| 0.1013        | 2.0   | 120  | 0.0996          | 0.8134    | 0.8677 | 0.8397 | 0.9649   |
+| 0.0694        | 3.0   | 180  | 0.0961          | 0.8295    | 0.8783 | 0.8532 | 0.9676   |
+| 0.0523        | 4.0   | 240  | 0.0861          | 0.9030    | 0.9198 | 0.9113 | 0.9762   |
+| 0.0309        | 5.0   | 300  | 0.0847          | 0.9088    | 0.9239 | 0.9163 | 0.9775   |
+| 0.0236        | 6.0   | 360  | 0.0950          | 0.9103    | 0.9253 | 0.9177 | 0.9772   |
+| 0.019         | 7.0   | 420  | 0.0974          | 0.9158    | 0.9277 | 0.9217 | 0.9775   |
+| 0.0153        | 8.0   | 480  | 0.0996          | 0.9139    | 0.9278 | 0.9208 | 0.9781   |
+| 0.0122        | 9.0   | 540  | 0.1029          | 0.9143    | 0.9284 | 0.9213 | 0.9781   |
+| 0.0104        | 10.0  | 600  | 0.1051          | 0.9154    | 0.9295 | 0.9224 | 0.9778   |
+
+
+### Framework versions
+
+- Transformers 4.39.3
+- Pytorch 2.1.2
+- Datasets 2.18.0
+- Tokenizers 0.15.2

config.json

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+{
+  "_name_or_path": "bayartsogt/mongolian-roberta-base",
+  "architectures": [
+    "RobertaForTokenClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": 0,
+  "classifier_dropout": null,
+  "eos_token_id": 2,
+  "finetuning_task": "ner",
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "O",
+    "1": "LOC",
+    "2": "MISC",
+    "3": "ORG",
+    "4": "PER"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "LOC": 1,
+    "MISC": 2,
+    "O": 0,
+    "ORG": 3,
+    "PER": 4
+  },
+  "layer_norm_eps": 1e-05,
+  "max_position_embeddings": 514,
+  "model_type": "roberta",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 1,
+  "position_embedding_type": "absolute",
+  "torch_dtype": "float32",
+  "transformers_version": "4.39.3",
+  "type_vocab_size": 1,
+  "use_cache": true,
+  "vocab_size": 50265
+}

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training_args.bin

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