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---
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
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