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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_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: 0.7890842332613391
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_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: 0.7825
- Accuracy: 0.7891
## 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: 20.0
### Training results
| Training Loss | Epoch | Step | Accuracy | Validation Loss |
|:-------------:|:-------:|:-----:|:--------:|:---------------:|
| 1.6067 | 0.9997 | 839 | 0.7197 | 1.8440 |
| 1.5433 | 1.9994 | 1678 | 0.7247 | 1.7661 |
| 1.4167 | 2.9991 | 2517 | 0.7310 | 1.6455 |
| 1.2948 | 4.0 | 3357 | 0.7366 | 1.5394 |
| 1.1715 | 4.9997 | 4196 | 0.7422 | 1.4463 |
| 1.0458 | 5.9994 | 5035 | 0.7484 | 1.3537 |
| 0.9357 | 6.9991 | 5874 | 0.7546 | 1.2456 |
| 0.8269 | 8.0 | 6714 | 0.7598 | 1.1735 |
| 0.7262 | 8.9997 | 7553 | 0.7649 | 1.0966 |
| 0.6381 | 9.9970 | 8390 | 0.7692 | 1.0623 |
| 0.5784 | 10.9997 | 9229 | 1.0101 | 0.7731 |
| 0.5071 | 11.9994 | 10068 | 0.9538 | 0.7760 |
| 0.4734 | 12.9991 | 10907 | 0.9292 | 0.7791 |
| 0.4302 | 14.0 | 11747 | 0.8846 | 0.7809 |
| 0.3917 | 14.9997 | 12586 | 0.8536 | 0.7833 |
| 0.3632 | 15.9994 | 13425 | 0.8468 | 0.7846 |
| 0.3351 | 16.9991 | 14264 | 0.8244 | 0.7863 |
| 0.3186 | 18.0 | 15104 | 0.8096 | 0.7871 |
| 0.2957 | 18.9997 | 15943 | 0.7865 | 0.7885 |
| 0.2858 | 19.9970 | 16780 | 0.7825 | 0.7891 |
### 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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