---
license: other
base_model: Qwen/Qwen1.5-4B
tags:
- generated_from_trainer
datasets:
- tyzhu/lmind_hotpot_train8000_eval7405_v1_doc_qa
metrics:
- accuracy
model-index:
- name: lmind_hotpot_train8000_eval7405_v1_doc_qa_Qwen_Qwen1.5-4B_3e-4_lora2
  results:
  - task:
      name: Causal Language Modeling
      type: text-generation
    dataset:
      name: tyzhu/lmind_hotpot_train8000_eval7405_v1_doc_qa
      type: tyzhu/lmind_hotpot_train8000_eval7405_v1_doc_qa
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.5165079365079365
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_doc_qa_Qwen_Qwen1.5-4B_3e-4_lora2

This model is a fine-tuned version of [Qwen/Qwen1.5-4B](https://huggingface.co/Qwen/Qwen1.5-4B) on the tyzhu/lmind_hotpot_train8000_eval7405_v1_doc_qa dataset.
It achieves the following results on the evaluation set:
- Loss: 3.1631
- Accuracy: 0.5165

## 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: 0.0003
- 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  | Validation Loss | Accuracy |
|:-------------:|:-------:|:-----:|:---------------:|:--------:|
| 1.7567        | 0.9998  | 1089  | 2.2626          | 0.5190   |
| 1.5617        | 1.9995  | 2178  | 2.2436          | 0.5246   |
| 1.343         | 2.9993  | 3267  | 2.3385          | 0.5237   |
| 1.1682        | 4.0     | 4357  | 2.4995          | 0.5215   |
| 1.0141        | 4.9998  | 5446  | 2.6397          | 0.5182   |
| 0.9023        | 5.9995  | 6535  | 2.7929          | 0.5170   |
| 0.8008        | 6.9993  | 7624  | 2.8233          | 0.5162   |
| 0.7377        | 8.0     | 8714  | 2.8833          | 0.5180   |
| 0.6732        | 8.9998  | 9803  | 2.9550          | 0.5165   |
| 0.6225        | 9.9995  | 10892 | 2.9767          | 0.5165   |
| 0.5858        | 10.9993 | 11981 | 3.0117          | 0.5165   |
| 0.5618        | 12.0    | 13071 | 3.0317          | 0.5170   |
| 0.5464        | 12.9998 | 14160 | 3.0686          | 0.5167   |
| 0.5243        | 13.9995 | 15249 | 3.0829          | 0.5149   |
| 0.5066        | 14.9993 | 16338 | 3.0958          | 0.5127   |
| 0.4947        | 16.0    | 17428 | 3.0921          | 0.5153   |
| 0.4841        | 16.9998 | 18517 | 3.1170          | 0.5162   |
| 0.4727        | 17.9995 | 19606 | 3.1375          | 0.5172   |
| 0.4634        | 18.9993 | 20695 | 3.1323          | 0.5150   |
| 0.4468        | 19.9954 | 21780 | 3.1631          | 0.5165   |


### Framework versions

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