End of training

README.md

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+---
+license: mit
+base_model: Amna100/PreTraining-MLM
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: fold_3
+  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. -->
+
+# fold_3
+
+This model is a fine-tuned version of [Amna100/PreTraining-MLM](https://huggingface.co/Amna100/PreTraining-MLM) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0085
+- Precision: 0.6966
+- Recall: 0.7188
+- F1: 0.7075
+- Accuracy: 0.9975
+
+## 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: 5
+- eval_batch_size: 5
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.0318        | 1.0   | 635  | 0.0095          | 0.6788    | 0.5942 | 0.6337 | 0.9973   |
+| 0.0114        | 2.0   | 1270 | 0.0093          | 0.6       | 0.7476 | 0.6657 | 0.9971   |
+| 0.0063        | 3.0   | 1905 | 0.0085          | 0.6966    | 0.7188 | 0.7075 | 0.9975   |
+
+
+### Framework versions
+
+- Transformers 4.37.0.dev0
+- Pytorch 2.1.0+cu121
+- Datasets 2.16.1
+- Tokenizers 0.15.0