---
license: other
base_model: Qwen/Qwen1.5-4B
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: lmind_hotpot_train8000_eval7405_v1_qa_Qwen_Qwen1.5-4B_lora2
  results: []
library_name: peft
---

<!-- 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. -->

# lmind_hotpot_train8000_eval7405_v1_qa_Qwen_Qwen1.5-4B_lora2

This model is a fine-tuned version of [Qwen/Qwen1.5-4B](https://huggingface.co/Qwen/Qwen1.5-4B) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.9177
- Accuracy: 0.4908

## 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: 1
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 20.0

### Training results

| Training Loss | Epoch | Step | Accuracy | Validation Loss |
|:-------------:|:-----:|:----:|:--------:|:---------------:|
| 2.2624        | 1.0   | 250  | 0.5159   | 2.3220          |
| 2.0942        | 2.0   | 500  | 0.5176   | 2.3289          |
| 1.8479        | 3.0   | 750  | 0.5148   | 2.3997          |
| 1.6153        | 4.0   | 1000 | 0.5107   | 2.5067          |
| 1.3618        | 5.0   | 1250 | 0.5052   | 2.6641          |
| 1.1477        | 6.0   | 1500 | 0.5016   | 2.8411          |
| 0.9248        | 7.0   | 1750 | 0.4978   | 3.0246          |
| 0.7705        | 8.0   | 2000 | 0.4954   | 3.2090          |
| 0.6344        | 9.0   | 2250 | 0.4935   | 3.3400          |
| 0.5612        | 10.0  | 2500 | 0.4926   | 3.4933          |
| 0.4967        | 11.0  | 2750 | 3.5794   | 0.4917          |
| 0.4696        | 12.0  | 3000 | 3.6326   | 0.4914          |
| 0.4399        | 13.0  | 3250 | 3.7408   | 0.4920          |
| 0.4324        | 14.0  | 3500 | 3.7450   | 0.4915          |
| 0.4105        | 15.0  | 3750 | 3.8301   | 0.4922          |
| 0.4081        | 16.0  | 4000 | 3.8488   | 0.4921          |
| 0.3939        | 17.0  | 4250 | 3.8492   | 0.4913          |
| 0.3924        | 18.0  | 4500 | 3.8751   | 0.4915          |
| 0.382         | 19.0  | 4750 | 3.9337   | 0.4910          |
| 0.3832        | 20.0  | 5000 | 3.9177   | 0.4908          |


### Framework versions

- PEFT 0.5.0
- Transformers 4.40.2
- Pytorch 2.3.0
- Datasets 2.19.1
- Tokenizers 0.19.1