---
library_name: transformers
license: other
base_model: Qwen/Qwen2.5-0.5B-Instruct
tags:
- llama-factory
- full
- generated_from_trainer
model-index:
- name: reranker_continuous_filt_train
  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. -->

# reranker_continuous_filt_train

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 reranker_continuous_filt_train dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2805

## 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 |
|:-------------:|:------:|:-----:|:---------------:|
| 0.2895        | 0.1000 | 2016  | 0.3479          |
| 0.2891        | 0.2000 | 4032  | 0.3320          |
| 0.396         | 0.3000 | 6048  | 0.3245          |
| 0.2693        | 0.4000 | 8064  | 0.3080          |
| 0.2712        | 0.5000 | 10080 | 0.3056          |
| 0.2738        | 0.6000 | 12096 | 0.2925          |
| 0.1629        | 0.7000 | 14112 | 0.2880          |
| 0.2761        | 0.8000 | 16128 | 0.2839          |
| 0.1861        | 0.9000 | 18144 | 0.2813          |


### Framework versions

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