Training complete

README.md

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+---
+library_name: transformers
+base_model: afmck/testing-llama-tiny
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: llma-finetuned-ner
+  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. -->
+
+# llma-finetuned-ner
+
+This model is a fine-tuned version of [afmck/testing-llama-tiny](https://huggingface.co/afmck/testing-llama-tiny) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1003
+- Precision: 0.9755
+- Recall: 0.9764
+- F1: 0.9759
+- Accuracy: 0.9815
+
+## 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: 8
+- eval_batch_size: 8
+- 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 |
+|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.0726        | 1.0   | 5285  | 0.1305          | 0.9820    | 0.9672 | 0.9745 | 0.9749   |
+| 0.0558        | 2.0   | 10570 | 0.1090          | 0.9733    | 0.9740 | 0.9737 | 0.9796   |
+| 0.07          | 3.0   | 15855 | 0.1003          | 0.9755    | 0.9764 | 0.9759 | 0.9815   |
+
+
+### Framework versions
+
+- Transformers 4.44.2
+- Pytorch 2.4.1+cu121
+- Datasets 3.0.1
+- Tokenizers 0.19.1