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---
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_3e-5_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: 0.7512829373650108
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_3e-5_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: 1.3258
- Accuracy: 0.7513
## 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: 3e-05
- 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 |
|:-------------:|:-------:|:-----:|:--------:|:---------------:|
| 1.6137 | 0.9997 | 839 | 0.7177 | 1.8264 |
| 1.5978 | 1.9994 | 1678 | 0.7190 | 1.8264 |
| 1.5493 | 2.9991 | 2517 | 0.7211 | 1.7810 |
| 1.5101 | 4.0 | 3357 | 0.7231 | 1.7413 |
| 1.4678 | 4.9997 | 4196 | 0.7247 | 1.7400 |
| 1.4236 | 5.9994 | 5035 | 0.7267 | 1.7019 |
| 1.3843 | 6.9991 | 5874 | 0.7286 | 1.6725 |
| 1.3481 | 8.0 | 6714 | 0.7304 | 1.6381 |
| 1.2954 | 8.9997 | 7553 | 0.7324 | 1.6103 |
| 1.2426 | 9.9994 | 8392 | 0.7338 | 1.5785 |
| 1.2169 | 10.9991 | 9231 | 0.7355 | 1.5435 |
| 1.167 | 12.0 | 10071 | 0.7375 | 1.5216 |
| 1.1276 | 12.9997 | 10910 | 0.7392 | 1.4949 |
| 1.0819 | 13.9994 | 11749 | 0.7406 | 1.4819 |
| 1.032 | 14.9991 | 12588 | 0.7426 | 1.4468 |
| 0.9981 | 15.9997 | 13424 | 1.4092 | 0.7443 |
| 0.9523 | 16.9994 | 14263 | 1.3949 | 0.7463 |
| 0.9281 | 17.9991 | 15102 | 1.3853 | 0.7477 |
| 0.8664 | 19.0 | 15942 | 1.3669 | 0.7496 |
| 0.8537 | 19.9985 | 16780 | 1.3258 | 0.7513 |
### 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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