yoruba-english-code-switching-lid

README.md

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+---
+library_name: transformers
+license: afl-3.0
+base_model: masakhane/afroxlmr-large-ner-masakhaner-1.0_2.0
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: yoruba-en-ner-model
+  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. -->
+
+# yoruba-en-ner-model
+
+This model is a fine-tuned version of [masakhane/afroxlmr-large-ner-masakhaner-1.0_2.0](https://huggingface.co/masakhane/afroxlmr-large-ner-masakhaner-1.0_2.0) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0212
+- Precision: 0.9907
+- Recall: 0.9906
+- F1: 0.9907
+- Accuracy: 0.9956
+
+## 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: 3e-05
+- train_batch_size: 64
+- eval_batch_size: 128
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 128
+- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss |
+|:-------------:|:-----:|:----:|:---------------:|
+| 0.1158        | 1.0   | 626  | 0.0240          |
+| 0.015         | 2.0   | 1252 | 0.0259          |
+| 0.0094        | 3.0   | 1878 | 0.0304          |
+| 0.0033        | 4.0   | 2504 | 0.0354          |
+| 0.002         | 5.0   | 3130 | 0.0377          |
+
+
+### Framework versions
+
+- Transformers 4.57.6
+- Pytorch 2.9.0+cu126
+- Datasets 4.0.0
+- Tokenizers 0.22.2

model.safetensors

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