---
license: other
base_model: Qwen/Qwen1.5-4B
tags:
- generated_from_trainer
datasets:
- tyzhu/lmind_nq_train6000_eval6489_v1_doc_qa_v3
metrics:
- accuracy
model-index:
- name: lmind_nq_train6000_eval6489_v1_doc_qa_v3_Qwen_Qwen1.5-4B_3e-4_lora2
  results:
  - task:
      name: Causal Language Modeling
      type: text-generation
    dataset:
      name: tyzhu/lmind_nq_train6000_eval6489_v1_doc_qa_v3
      type: tyzhu/lmind_nq_train6000_eval6489_v1_doc_qa_v3
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.5640512820512821
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_doc_qa_v3_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_nq_train6000_eval6489_v1_doc_qa_v3 dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2532
- Accuracy: 0.5641

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.8369        | 1.0   | 529   | 1.6032          | 0.5751   |
| 1.6451        | 2.0   | 1058  | 1.6357          | 0.5746   |
| 1.3703        | 3.0   | 1587  | 1.7677          | 0.5716   |
| 1.1817        | 4.0   | 2116  | 1.8587          | 0.5718   |
| 0.9674        | 5.0   | 2645  | 1.9319          | 0.5713   |
| 0.7936        | 6.0   | 3174  | 1.9934          | 0.5704   |
| 0.67          | 7.0   | 3703  | 2.0467          | 0.5684   |
| 0.5604        | 8.0   | 4232  | 2.1218          | 0.5693   |
| 0.4747        | 9.0   | 4761  | 2.1342          | 0.5682   |
| 0.4191        | 10.0  | 5290  | 2.1679          | 0.5674   |
| 0.3971        | 11.0  | 5819  | 2.2081          | 0.5658   |
| 0.3753        | 12.0  | 6348  | 2.1840          | 0.5664   |
| 0.3571        | 13.0  | 6877  | 2.2324          | 0.5634   |
| 0.3526        | 14.0  | 7406  | 2.2190          | 0.5632   |
| 0.35          | 15.0  | 7935  | 2.2086          | 0.5639   |
| 0.3323        | 16.0  | 8464  | 2.2655          | 0.5654   |
| 0.3281        | 17.0  | 8993  | 2.2444          | 0.5667   |
| 0.3328        | 18.0  | 9522  | 2.2597          | 0.5626   |
| 0.3305        | 19.0  | 10051 | 2.2682          | 0.5633   |
| 0.3228        | 20.0  | 10580 | 2.2532          | 0.5641   |


### Framework versions

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