---
license: other
base_model: Qwen/Qwen1.5-4B
tags:
- generated_from_trainer
datasets:
- tyzhu/lmind_nq_train6000_eval6489_v1_qa
metrics:
- accuracy
model-index:
- name: lmind_nq_train6000_eval6489_v1_qa_Qwen_Qwen1.5-4B_lora2
  results:
  - task:
      name: Causal Language Modeling
      type: text-generation
    dataset:
      name: tyzhu/lmind_nq_train6000_eval6489_v1_qa
      type: tyzhu/lmind_nq_train6000_eval6489_v1_qa
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.5594358974358974
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_nq_train6000_eval6489_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 the tyzhu/lmind_nq_train6000_eval6489_v1_qa dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2527
- Accuracy: 0.5594

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 1.7657        | 0.9973 | 187  | 1.6215          | 0.5738   |
| 1.497         | 2.0    | 375  | 1.6180          | 0.5742   |
| 1.2345        | 2.9973 | 562  | 1.6951          | 0.5713   |
| 1.0084        | 4.0    | 750  | 1.8059          | 0.5659   |
| 0.8397        | 4.9973 | 937  | 1.9245          | 0.5647   |
| 0.7186        | 6.0    | 1125 | 2.0345          | 0.5614   |
| 0.6421        | 6.9973 | 1312 | 2.1148          | 0.5608   |
| 0.5968        | 8.0    | 1500 | 2.1779          | 0.5585   |
| 0.5417        | 8.9973 | 1687 | 2.2654          | 0.5568   |
| 0.5356        | 9.9733 | 1870 | 2.2527          | 0.5594   |


### Framework versions

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