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---
license: other
base_model: Qwen/Qwen1.5-4B
tags:
- generated_from_trainer
datasets:
- tyzhu/lmind_hotpot_train8000_eval7405_v1_doc_qa
metrics:
- accuracy
model-index:
- name: lmind_hotpot_train8000_eval7405_v1_doc_qa_Qwen_Qwen1.5-4B_3e-4_lora2
results:
- task:
name: Causal Language Modeling
type: text-generation
dataset:
name: tyzhu/lmind_hotpot_train8000_eval7405_v1_doc_qa
type: tyzhu/lmind_hotpot_train8000_eval7405_v1_doc_qa
metrics:
- name: Accuracy
type: accuracy
value: 0.5165079365079365
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_doc_qa_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_hotpot_train8000_eval7405_v1_doc_qa dataset.
It achieves the following results on the evaluation set:
- Loss: 3.1631
- Accuracy: 0.5165
## 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 |
|:-------------:|:-------:|:-----:|:---------------:|:--------:|
| 1.7567 | 0.9998 | 1089 | 2.2626 | 0.5190 |
| 1.5617 | 1.9995 | 2178 | 2.2436 | 0.5246 |
| 1.343 | 2.9993 | 3267 | 2.3385 | 0.5237 |
| 1.1682 | 4.0 | 4357 | 2.4995 | 0.5215 |
| 1.0141 | 4.9998 | 5446 | 2.6397 | 0.5182 |
| 0.9023 | 5.9995 | 6535 | 2.7929 | 0.5170 |
| 0.8008 | 6.9993 | 7624 | 2.8233 | 0.5162 |
| 0.7377 | 8.0 | 8714 | 2.8833 | 0.5180 |
| 0.6732 | 8.9998 | 9803 | 2.9550 | 0.5165 |
| 0.6225 | 9.9995 | 10892 | 2.9767 | 0.5165 |
| 0.5858 | 10.9993 | 11981 | 3.0117 | 0.5165 |
| 0.5618 | 12.0 | 13071 | 3.0317 | 0.5170 |
| 0.5464 | 12.9998 | 14160 | 3.0686 | 0.5167 |
| 0.5243 | 13.9995 | 15249 | 3.0829 | 0.5149 |
| 0.5066 | 14.9993 | 16338 | 3.0958 | 0.5127 |
| 0.4947 | 16.0 | 17428 | 3.0921 | 0.5153 |
| 0.4841 | 16.9998 | 18517 | 3.1170 | 0.5162 |
| 0.4727 | 17.9995 | 19606 | 3.1375 | 0.5172 |
| 0.4634 | 18.9993 | 20695 | 3.1323 | 0.5150 |
| 0.4468 | 19.9954 | 21780 | 3.1631 | 0.5165 |
### 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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