---
library_name: transformers
license: other
base_model: Qwen/Qwen2.5-1.5B-Instruct
tags:
- llama-factory
- full
- generated_from_trainer
model-index:
- name: fulltrain_filtered_1dot5
  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. -->

# fulltrain_filtered_1dot5

This model is a fine-tuned version of [Qwen/Qwen2.5-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct) on the reranker_fulltrain_filtered dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0437

## 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: 1e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 8
- total_eval_batch_size: 8
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.01
- num_epochs: 1.0

### Training results

| Training Loss | Epoch  | Step  | Validation Loss |
|:-------------:|:------:|:-----:|:---------------:|
| 0.0647        | 0.1000 | 2055  | 0.0842          |
| 0.0689        | 0.2000 | 4110  | 0.0686          |
| 0.0829        | 0.3000 | 6165  | 0.0686          |
| 0.0721        | 0.4001 | 8220  | 0.0597          |
| 0.0453        | 0.5001 | 10275 | 0.0543          |
| 0.0436        | 0.6001 | 12330 | 0.0499          |
| 0.0657        | 0.7001 | 14385 | 0.0492          |
| 0.0669        | 0.8001 | 16440 | 0.0456          |
| 0.0594        | 0.9001 | 18495 | 0.0438          |


### Framework versions

- Transformers 4.46.1
- Pytorch 2.4.0+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3