---
license: llama3
base_model: AI-Sweden-Models/Llama-3-8B-instruct
tags:
- generated_from_trainer
metrics:
- accuracy
library_name: peft
model-index:
- name: llm2vec-da-mntp
  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. -->

# llm2vec-da-mntp

This model is a fine-tuned version of [AI-Sweden-Models/Llama-3-8B-instruct](https://huggingface.co/AI-Sweden-Models/Llama-3-8B-instruct) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8092
- Accuracy: 0.8176

## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| No log        | 0.0626 | 250  | 1.4498          | 0.7011   |
| 1.7757        | 0.1252 | 500  | 1.1587          | 0.7524   |
| 1.7757        | 0.1878 | 750  | 1.0504          | 0.7711   |
| 1.0486        | 0.2504 | 1000 | 0.9868          | 0.7832   |
| 1.0486        | 0.3130 | 1250 | 0.9451          | 0.7912   |
| 0.9401        | 0.3757 | 1500 | 0.9140          | 0.7969   |
| 0.9401        | 0.4383 | 1750 | 0.8904          | 0.8020   |
| 0.8842        | 0.5009 | 2000 | 0.8662          | 0.8071   |
| 0.8842        | 0.5635 | 2250 | 0.8535          | 0.8086   |
| 0.8473        | 0.6261 | 2500 | 0.8301          | 0.8134   |
| 0.8473        | 0.6887 | 2750 | 0.8179          | 0.8158   |
| 0.8188        | 0.7513 | 3000 | 0.8092          | 0.8176   |


### Framework versions

- PEFT 0.13.2
- Transformers 4.40.2
- Pytorch 2.5.1+cu124
- Datasets 2.19.2
- Tokenizers 0.19.1