---
license: other
base_model: Qwen/Qwen1.5-4B
tags:
- generated_from_trainer
datasets:
- tyzhu/lmind_hotpot_train8000_eval7405_v1_docidx
metrics:
- accuracy
model-index:
- name: lmind_hotpot_train8000_eval7405_v1_docidx_Qwen_Qwen1.5-4B_lora2
  results:
  - task:
      name: Causal Language Modeling
      type: text-generation
    dataset:
      name: tyzhu/lmind_hotpot_train8000_eval7405_v1_docidx
      type: tyzhu/lmind_hotpot_train8000_eval7405_v1_docidx
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.7691922246220302
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_docidx_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 the tyzhu/lmind_hotpot_train8000_eval7405_v1_docidx dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0623
- Accuracy: 0.7692

## 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: 10.0

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 1.6067        | 0.9997 | 839  | 1.8440          | 0.7197   |
| 1.5433        | 1.9994 | 1678 | 1.7661          | 0.7247   |
| 1.4167        | 2.9991 | 2517 | 1.6455          | 0.7310   |
| 1.2948        | 4.0    | 3357 | 1.5394          | 0.7366   |
| 1.1715        | 4.9997 | 4196 | 1.4463          | 0.7422   |
| 1.0458        | 5.9994 | 5035 | 1.3537          | 0.7484   |
| 0.9357        | 6.9991 | 5874 | 1.2456          | 0.7546   |
| 0.8269        | 8.0    | 6714 | 1.1735          | 0.7598   |
| 0.7262        | 8.9997 | 7553 | 1.0966          | 0.7649   |
| 0.6381        | 9.9970 | 8390 | 1.0623          | 0.7692   |


### Framework versions

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