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---
license: llama2
library_name: peft
tags:
- generated_from_trainer
base_model: meta-llama/Llama-2-13b-hf
metrics:
- accuracy
- precision
- recall
model-index:
- name: llama2-13B_MT
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. -->
# llama2-13B_MT
This model is a fine-tuned version of [meta-llama/Llama-2-13b-hf](https://huggingface.co/meta-llama/Llama-2-13b-hf) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5717
- Accuracy: 0.7967
- Precision: 0.8296
- Recall: 0.7467
- F1 score: 0.7860
## 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: 0.0001
- 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 | Accuracy | F1 score | Precision | Recall | Validation Loss |
|:-------------:|:-----:|:----:|:--------:|:--------:|:---------:|:------:|:---------------:|
| 0.6169 | 0.25 | 200 | 0.735 | 0.7145 | 0.7743 | 0.6633 | 0.5712 |
| 0.5218 | 0.5 | 400 | 0.765 | 0.7487 | 0.8046 | 0.7 | 0.5406 |
| 0.4976 | 0.75 | 600 | 0.7717 | 0.7486 | 0.8327 | 0.68 | 0.4991 |
| 0.4531 | 1.0 | 800 | 0.7567 | 0.7045 | 0.8969 | 0.58 | 0.5727 |
| 0.339 | 1.25 | 1000 | 0.6176 | 0.7617 | 0.9198 | 0.5733 | 0.7064 |
| 0.3046 | 1.5 | 1200 | 0.5150 | 0.7767 | 0.7964 | 0.7433 | 0.7690 |
| 0.3363 | 1.75 | 1400 | 0.5185 | 0.795 | 0.8554 | 0.71 | 0.7760 |
| 0.3074 | 2.0 | 1600 | 0.4635 | 0.79 | 0.7862 | 0.7967 | 0.7914 |
| 0.2052 | 2.25 | 1800 | 0.5411 | 0.8 | 0.8659 | 0.71 | 0.7802 |
| 0.1841 | 2.5 | 2000 | 0.5959 | 0.8033 | 0.8889 | 0.6933 | 0.7790 |
| 0.1629 | 2.75 | 2200 | 0.5510 | 0.7933 | 0.8143 | 0.76 | 0.7862 |
| 0.1559 | 3.0 | 2400 | 0.5717 | 0.7967 | 0.8296 | 0.7467 | 0.7860 |
### Framework versions
- PEFT 0.11.1
- Transformers 4.44.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1 |