---
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