Training complete

README.md

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+---
+license: mit
+base_model: Davlan/afro-xlmr-base
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: angela_punc_untranslated_eval
+  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. -->
+
+# angela_punc_untranslated_eval
+
+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: 0.1902
+- Precision: 0.3889
+- Recall: 0.2568
+- F1: 0.3093
+- Accuracy: 0.9517
+
+## 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: 5e-05
+- train_batch_size: 16
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.1524        | 1.0   | 1283 | 0.1547          | 0.4163    | 0.1471 | 0.2174 | 0.9546   |
+| 0.1295        | 2.0   | 2566 | 0.1518          | 0.4489    | 0.1943 | 0.2712 | 0.9556   |
+| 0.1113        | 3.0   | 3849 | 0.1614          | 0.4152    | 0.2323 | 0.2979 | 0.9538   |
+| 0.0896        | 4.0   | 5132 | 0.1784          | 0.4248    | 0.2346 | 0.3023 | 0.9542   |
+| 0.073         | 5.0   | 6415 | 0.1902          | 0.3889    | 0.2568 | 0.3093 | 0.9517   |
+
+
+### Framework versions
+
+- Transformers 4.32.0
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.4
+- Tokenizers 0.13.3