metadata
license: other
base_model: Qwen/Qwen1.5-4B
tags:
- generated_from_trainer
datasets:
- tyzhu/lmind_hotpot_train8000_eval7405_v1_qa
metrics:
- accuracy
model-index:
- name: lmind_hotpot_train8000_eval7405_v1_qa_Qwen_Qwen1.5-4B_5e-4_lora2
results:
- task:
name: Causal Language Modeling
type: text-generation
dataset:
name: tyzhu/lmind_hotpot_train8000_eval7405_v1_qa
type: tyzhu/lmind_hotpot_train8000_eval7405_v1_qa
metrics:
- name: Accuracy
type: accuracy
value: 0.48644444444444446
library_name: peft
lmind_hotpot_train8000_eval7405_v1_qa_Qwen_Qwen1.5-4B_5e-4_lora2
This model is a fine-tuned version of Qwen/Qwen1.5-4B on the tyzhu/lmind_hotpot_train8000_eval7405_v1_qa dataset. It achieves the following results on the evaluation set:
- Loss: 3.7344
- Accuracy: 0.4864
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: 0.0005
- 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 |
|---|---|---|---|---|
| 2.252 | 1.0 | 250 | 2.3165 | 0.5171 |
| 1.8363 | 2.0 | 500 | 2.4264 | 0.5127 |
| 1.3801 | 3.0 | 750 | 2.6120 | 0.5059 |
| 1.0246 | 4.0 | 1000 | 2.8617 | 0.5008 |
| 0.7286 | 5.0 | 1250 | 3.0953 | 0.4959 |
| 0.601 | 6.0 | 1500 | 3.2139 | 0.4950 |
| 0.5138 | 7.0 | 1750 | 3.2912 | 0.4933 |
| 0.4837 | 8.0 | 2000 | 3.4517 | 0.49 |
| 0.4506 | 9.0 | 2250 | 3.4107 | 0.4911 |
| 0.4578 | 10.0 | 2500 | 3.4786 | 0.4905 |
| 0.4362 | 11.0 | 2750 | 3.5410 | 0.4899 |
| 0.4429 | 12.0 | 3000 | 3.5656 | 0.4909 |
| 0.4366 | 13.0 | 3250 | 3.5425 | 0.4890 |
| 0.4474 | 14.0 | 3500 | 3.5998 | 0.4900 |
| 0.4283 | 15.0 | 3750 | 3.6044 | 0.4870 |
| 0.4299 | 16.0 | 4000 | 3.6720 | 0.4882 |
| 0.4202 | 17.0 | 4250 | 3.6220 | 0.4860 |
| 0.4318 | 18.0 | 4500 | 3.6682 | 0.4875 |
| 0.4151 | 19.0 | 4750 | 3.7105 | 0.4857 |
| 0.4227 | 20.0 | 5000 | 3.7344 | 0.4864 |
Framework versions
- PEFT 0.5.0
- Transformers 4.40.2
- Pytorch 2.3.0
- Datasets 2.19.1
- Tokenizers 0.19.1