End of training

README.md

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 ---
-license: mit
+library_name: peft
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+base_model: NousResearch/Llama-2-7b-hf
+model-index:
+- name: billm-llama-7b-conll03-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. -->
+
+# billm-llama-7b-conll03-ner
+
+This model is a fine-tuned version of [NousResearch/Llama-2-7b-hf](https://huggingface.co/NousResearch/Llama-2-7b-hf) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1894
+- Precision: 0.9228
+- Recall: 0.9364
+- F1: 0.9296
+- Accuracy: 0.9861
+
+## 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: 0.0002
+- 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: 10
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.0453        | 1.0   | 1756  | 0.1025          | 0.9064    | 0.9227 | 0.9145 | 0.9836   |
+| 0.0204        | 2.0   | 3512  | 0.0932          | 0.9187    | 0.9258 | 0.9222 | 0.9846   |
+| 0.0105        | 3.0   | 5268  | 0.1267          | 0.9183    | 0.9308 | 0.9245 | 0.9855   |
+| 0.0039        | 4.0   | 7024  | 0.1680          | 0.9213    | 0.9384 | 0.9298 | 0.9861   |
+| 0.0014        | 5.0   | 8780  | 0.1761          | 0.9228    | 0.9366 | 0.9297 | 0.9861   |
+| 0.0008        | 6.0   | 10536 | 0.1835          | 0.9228    | 0.9361 | 0.9294 | 0.9861   |
+| 0.0005        | 7.0   | 12292 | 0.1880          | 0.9233    | 0.9363 | 0.9297 | 0.9861   |
+| 0.0003        | 8.0   | 14048 | 0.1893          | 0.9230    | 0.9368 | 0.9298 | 0.9861   |
+| 0.0003        | 9.0   | 15804 | 0.1895          | 0.9228    | 0.9364 | 0.9296 | 0.9861   |
+| 0.0002        | 10.0  | 17560 | 0.1894          | 0.9228    | 0.9364 | 0.9296 | 0.9861   |
+
+
+### Framework versions
+
+- PEFT 0.9.0
+- Transformers 4.38.2
+- Pytorch 2.0.1
+- Datasets 2.16.0
+- Tokenizers 0.15.0

adapter_model.safetensors

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