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---
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: 0.1783
- Precision: 0.9150
- Recall: 0.9330
- F1: 0.9239
- Accuracy: 0.9851
## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0477 | 1.0 | 1756 | 0.0998 | 0.9116 | 0.9283 | 0.9199 | 0.9842 |
| 0.0201 | 2.0 | 3512 | 0.0986 | 0.9152 | 0.9251 | 0.9201 | 0.9842 |
| 0.0089 | 3.0 | 5268 | 0.1195 | 0.9128 | 0.9278 | 0.9202 | 0.9843 |
| 0.0025 | 4.0 | 7024 | 0.1564 | 0.9129 | 0.9341 | 0.9234 | 0.9851 |
| 0.0013 | 5.0 | 8780 | 0.1669 | 0.9140 | 0.9316 | 0.9227 | 0.9850 |
| 0.0006 | 6.0 | 10536 | 0.1736 | 0.9155 | 0.9328 | 0.9241 | 0.9852 |
| 0.0003 | 7.0 | 12292 | 0.1755 | 0.9144 | 0.9325 | 0.9233 | 0.9851 |
| 0.0003 | 8.0 | 14048 | 0.1782 | 0.9145 | 0.9328 | 0.9236 | 0.9851 |
| 0.0003 | 9.0 | 15804 | 0.1782 | 0.9144 | 0.9326 | 0.9234 | 0.9851 |
| 0.0002 | 10.0 | 17560 | 0.1783 | 0.9150 | 0.9330 | 0.9239 | 0.9851 |
### Framework versions
- PEFT 0.9.0
- Transformers 4.38.2
- Pytorch 2.0.1
- Datasets 2.16.0
- Tokenizers 0.15.0 |