---
license: apache-2.0
base_model: Qwen/Qwen2.5-0.5B-Instruct
tags:
- generated_from_trainer
datasets:
- wikitext
metrics:
- accuracy
model-index:
- name: llm2vec-qwen2.5-0.5-instruct
  results:
  - task:
      name: Masked Language Modeling
      type: fill-mask
    dataset:
      name: wikitext wikitext-103-raw-v1
      type: wikitext
      args: wikitext-103-raw-v1
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.629556877924779
---

<!-- 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-qwen2.5-0.5-instruct

This model is a fine-tuned version of [Qwen/Qwen2.5-0.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-0.5B-Instruct) on the wikitext wikitext-103-raw-v1 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8264
- Accuracy: 0.6296

## 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: 16
- 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        | 0.0083 | 100  | 2.3376          | 0.5511   |
| No log        | 0.0166 | 200  | 2.1736          | 0.5765   |
| No log        | 0.0248 | 300  | 2.0679          | 0.5930   |
| No log        | 0.0331 | 400  | 1.9839          | 0.6056   |
| 2.2761        | 0.0414 | 500  | 1.9611          | 0.6085   |
| 2.2761        | 0.0497 | 600  | 1.9054          | 0.6203   |
| 2.2761        | 0.0580 | 700  | 1.8838          | 0.6242   |
| 2.2761        | 0.0662 | 800  | 1.8403          | 0.6296   |
| 2.2761        | 0.0745 | 900  | 1.8235          | 0.6300   |
| 1.8887        | 0.0828 | 1000 | 1.7920          | 0.6351   |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1