metadata
license: other
base_model: Qwen/Qwen1.5-4B
tags:
- generated_from_trainer
datasets:
- tyzhu/lmind_hotpot_train8000_eval7405_v1_reciteonly_qa
metrics:
- accuracy
model-index:
- name: >-
lmind_hotpot_train8000_eval7405_v1_reciteonly_qa_Qwen_Qwen1.5-4B_3e-5_lora2
results:
- task:
name: Causal Language Modeling
type: text-generation
dataset:
name: tyzhu/lmind_hotpot_train8000_eval7405_v1_reciteonly_qa
type: tyzhu/lmind_hotpot_train8000_eval7405_v1_reciteonly_qa
metrics:
- name: Accuracy
type: accuracy
value: 0.6657583697234353
library_name: peft
lmind_hotpot_train8000_eval7405_v1_reciteonly_qa_Qwen_Qwen1.5-4B_3e-5_lora2
This model is a fine-tuned version of Qwen/Qwen1.5-4B on the tyzhu/lmind_hotpot_train8000_eval7405_v1_reciteonly_qa dataset. It achieves the following results on the evaluation set:
- Loss: 1.8696
- Accuracy: 0.6658
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 | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.4742 | 1.0 | 250 | 1.5313 | 0.6748 |
| 1.45 | 2.0 | 500 | 1.5196 | 0.6757 |
| 1.4269 | 3.0 | 750 | 1.5134 | 0.6761 |
| 1.3999 | 4.0 | 1000 | 1.5120 | 0.6762 |
| 1.3614 | 5.0 | 1250 | 1.5192 | 0.6760 |
| 1.3303 | 6.0 | 1500 | 1.5266 | 0.6755 |
| 1.2946 | 7.0 | 1750 | 1.5446 | 0.6747 |
| 1.2518 | 8.0 | 2000 | 1.5590 | 0.6745 |
| 1.2082 | 9.0 | 2250 | 1.5717 | 0.6740 |
| 1.19 | 10.0 | 2500 | 1.6022 | 0.6727 |
| 1.1523 | 11.0 | 2750 | 1.6098 | 0.6726 |
| 1.1193 | 12.0 | 3000 | 1.6345 | 0.6716 |
| 1.0736 | 13.0 | 3250 | 1.6748 | 0.6707 |
| 1.0414 | 14.0 | 3500 | 1.6880 | 0.6701 |
| 1.0069 | 15.0 | 3750 | 1.7182 | 0.6694 |
| 0.9654 | 16.0 | 4000 | 1.7522 | 0.6685 |
| 0.9337 | 17.0 | 4250 | 1.7826 | 0.6677 |
| 0.9 | 18.0 | 4500 | 1.8080 | 0.6672 |
| 0.8704 | 19.0 | 4750 | 1.8350 | 0.6663 |
| 0.8407 | 20.0 | 5000 | 1.8696 | 0.6658 |
Framework versions
- PEFT 0.5.0
- Transformers 4.40.2
- Pytorch 2.3.0
- Datasets 2.19.1
- Tokenizers 0.19.1