Uploading checkpoint-16500 for mbert - yor-latn

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: google-bert/bert-base-multilingual-cased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: yor-Latn
+  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. -->
+
+# yor-Latn
+
+This model is a fine-tuned version of [google-bert/bert-base-multilingual-cased](https://huggingface.co/google-bert/bert-base-multilingual-cased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.7111
+- Accuracy: 0.8622
+
+## 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: 0.0001
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 2
+- total_train_batch_size: 32
+- total_eval_batch_size: 32
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- training_steps: 100000
+
+
+    ### Citation Information
+
+    If you use this model in your work, please cite the following paper. Additionally, if you require more details on training and performance, refer to the paper:
+
+    @misc{gurgurov2025smallmodelsbigimpact,
+        title={Small Models, Big Impact: Efficient Corpus and Graph-Based Adaptation of Small Multilingual Language Models for Low-Resource Languages}, 
+        author={Daniil Gurgurov and Ivan Vykopal and Josef van Genabith and Simon Ostermann},
+        year={2025},
+        eprint={2502.10140},
+        archivePrefix={arXiv},
+        primaryClass={cs.CL},
+        url={https://arxiv.org/abs/2502.10140}, 
+    }
+    

config.json

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+  "position_embedding_type": "absolute",
+  "torch_dtype": "float32",
+  "transformers_version": "4.45.2",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 119547
+}

generation_config.json

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+  "_from_model_config": true,
+  "pad_token_id": 0,
+  "transformers_version": "4.45.2"
+}

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special_tokens_map.json

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tokenizer_config.json

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