Model save

README.md

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+---
+library_name: transformers
+license: mit
+base_model: Davlan/afro-xlmr-base
+tags:
+- generated_from_trainer
+metrics:
+- f1
+- accuracy
+model-index:
+- name: afro-xlmr-base-afr-finetuned-augmentation-LUNAR
+  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. -->
+
+# afro-xlmr-base-afr-finetuned-augmentation-LUNAR
+
+This model is a fine-tuned version of [Davlan/afro-xlmr-base](https://huggingface.co/Davlan/afro-xlmr-base) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2889
+- F1: 0.4089
+- Roc Auc: 0.6608
+- Accuracy: 0.6678
+
+## 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: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 100
+- num_epochs: 20
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
+| 0.4289        | 1.0   | 76   | 0.3283          | 0.0    | 0.5     | 0.3520   |
+| 0.3509        | 2.0   | 152  | 0.3160          | 0.1005 | 0.5277  | 0.4836   |
+| 0.2864        | 3.0   | 228  | 0.2631          | 0.2532 | 0.5927  | 0.5855   |
+| 0.2383        | 4.0   | 304  | 0.2411          | 0.2210 | 0.5799  | 0.5559   |
+| 0.1902        | 5.0   | 380  | 0.2632          | 0.2619 | 0.5909  | 0.5921   |
+| 0.1545        | 6.0   | 456  | 0.2466          | 0.3297 | 0.6281  | 0.6612   |
+| 0.1408        | 7.0   | 532  | 0.2407          | 0.3469 | 0.6253  | 0.6447   |
+| 0.1087        | 8.0   | 608  | 0.2463          | 0.3989 | 0.6645  | 0.6809   |
+| 0.0743        | 9.0   | 684  | 0.2497          | 0.4086 | 0.6561  | 0.6711   |
+| 0.0832        | 10.0  | 760  | 0.2581          | 0.4063 | 0.6516  | 0.6908   |
+| 0.0599        | 11.0  | 836  | 0.2583          | 0.4992 | 0.6911  | 0.7007   |
+| 0.0553        | 12.0  | 912  | 0.2755          | 0.5012 | 0.6931  | 0.6908   |
+| 0.0497        | 13.0  | 988  | 0.2741          | 0.4253 | 0.6688  | 0.6809   |
+| 0.029         | 14.0  | 1064 | 0.2864          | 0.4033 | 0.6529  | 0.6776   |
+| 0.0349        | 15.0  | 1140 | 0.3034          | 0.4742 | 0.6808  | 0.6776   |
+| 0.0249        | 16.0  | 1216 | 0.2889          | 0.4089 | 0.6608  | 0.6678   |
+
+
+### Framework versions
+
+- Transformers 4.45.1
+- Pytorch 2.4.0
+- Datasets 3.0.1
+- Tokenizers 0.20.0

model.safetensors

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