---
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: 0.7890842332613391
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: 0.7825
- Accuracy: 0.7891

## 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 |
|:-------------:|:-------:|:-----:|:--------:|:---------------:|
| 1.6067        | 0.9997  | 839   | 0.7197   | 1.8440          |
| 1.5433        | 1.9994  | 1678  | 0.7247   | 1.7661          |
| 1.4167        | 2.9991  | 2517  | 0.7310   | 1.6455          |
| 1.2948        | 4.0     | 3357  | 0.7366   | 1.5394          |
| 1.1715        | 4.9997  | 4196  | 0.7422   | 1.4463          |
| 1.0458        | 5.9994  | 5035  | 0.7484   | 1.3537          |
| 0.9357        | 6.9991  | 5874  | 0.7546   | 1.2456          |
| 0.8269        | 8.0     | 6714  | 0.7598   | 1.1735          |
| 0.7262        | 8.9997  | 7553  | 0.7649   | 1.0966          |
| 0.6381        | 9.9970  | 8390  | 0.7692   | 1.0623          |
| 0.5784        | 10.9997 | 9229  | 1.0101   | 0.7731          |
| 0.5071        | 11.9994 | 10068 | 0.9538   | 0.7760          |
| 0.4734        | 12.9991 | 10907 | 0.9292   | 0.7791          |
| 0.4302        | 14.0    | 11747 | 0.8846   | 0.7809          |
| 0.3917        | 14.9997 | 12586 | 0.8536   | 0.7833          |
| 0.3632        | 15.9994 | 13425 | 0.8468   | 0.7846          |
| 0.3351        | 16.9991 | 14264 | 0.8244   | 0.7863          |
| 0.3186        | 18.0    | 15104 | 0.8096   | 0.7871          |
| 0.2957        | 18.9997 | 15943 | 0.7865   | 0.7885          |
| 0.2858        | 19.9970 | 16780 | 0.7825   | 0.7891          |


### Framework versions

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