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-demo
+  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-demo
+
+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: 0.1566
+- Precision: 0.6857
+- Recall: 0.7725
+- F1: 0.7265
+- Accuracy: 0.9453
+
+## 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: 16
+- eval_batch_size: 32
+- 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 |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.9745        | 1.0   | 477  | 0.5080          | 0.2164    | 0.1205 | 0.1548 | 0.8187   |
+| 0.425         | 2.0   | 954  | 0.3128          | 0.5213    | 0.5929 | 0.5548 | 0.9038   |
+| 0.2943        | 3.0   | 1431 | 0.2337          | 0.5905    | 0.6781 | 0.6313 | 0.9237   |
+| 0.2393        | 4.0   | 1908 | 0.2000          | 0.6303    | 0.7224 | 0.6732 | 0.9333   |
+| 0.2134        | 5.0   | 2385 | 0.1813          | 0.6526    | 0.7434 | 0.6951 | 0.9384   |
+| 0.1978        | 6.0   | 2862 | 0.1704          | 0.6629    | 0.7527 | 0.7050 | 0.9412   |
+| 0.1885        | 7.0   | 3339 | 0.1647          | 0.6737    | 0.7625 | 0.7154 | 0.9429   |
+| 0.1823        | 8.0   | 3816 | 0.1595          | 0.6816    | 0.7680 | 0.7222 | 0.9443   |
+| 0.1792        | 9.0   | 4293 | 0.1576          | 0.6843    | 0.7713 | 0.7252 | 0.9451   |
+| 0.1778        | 10.0  | 4770 | 0.1566          | 0.6857    | 0.7725 | 0.7265 | 0.9453   |
+
+
+### Framework versions
+
+- Transformers 4.40.1
+- Pytorch 2.2.1+cu121
+- Datasets 2.19.0
+- Tokenizers 0.19.1

model.safetensors

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runs/May02_12-32-40_37c6c603935c/events.out.tfevents.1714653170.37c6c603935c.1342.0

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special_tokens_map.json

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+{
+  "bos_token": {
+    "content": "<s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
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+  "cls_token": {
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+    "lstrip": false,
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+    "rstrip": false,
+    "single_word": false
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+}

tokenizer_config.json

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+{
+  "add_prefix_space": true,
+  "added_tokens_decoder": {
+    "0": {
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+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
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+  "clean_up_tokenization_spaces": true,
+  "cls_token": "<s>",
+  "eos_token": "</s>",
+  "errors": "replace",
+  "mask_token": "<mask>",
+  "model_max_length": 1000000000000000019884624838656,
+  "pad_token": "<pad>",
+  "sep_token": "</s>",
+  "tokenizer_class": "RobertaTokenizer",
+  "trim_offsets": true,
+  "unk_token": "<unk>"
+}

training_args.bin

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