metadata
license: other
base_model: Qwen/Qwen1.5-4B
tags:
- generated_from_trainer
datasets:
- tyzhu/lmind_nq_train6000_eval6489_v1_doc_qa_v3
metrics:
- accuracy
model-index:
- name: lmind_nq_train6000_eval6489_v1_doc_qa_v3_Qwen_Qwen1.5-4B_5e-5_lora2
results:
- task:
name: Causal Language Modeling
type: text-generation
dataset:
name: tyzhu/lmind_nq_train6000_eval6489_v1_doc_qa_v3
type: tyzhu/lmind_nq_train6000_eval6489_v1_doc_qa_v3
metrics:
- name: Accuracy
type: accuracy
value: 0.5608717948717948
library_name: peft
lmind_nq_train6000_eval6489_v1_doc_qa_v3_Qwen_Qwen1.5-4B_5e-5_lora2
This model is a fine-tuned version of Qwen/Qwen1.5-4B on the tyzhu/lmind_nq_train6000_eval6489_v1_doc_qa_v3 dataset. It achieves the following results on the evaluation set:
- Loss: 2.5129
- Accuracy: 0.5609
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: 5e-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 |
|---|---|---|---|---|
| 1.843 | 1.0 | 529 | 1.6193 | 0.5738 |
| 1.7946 | 2.0 | 1058 | 1.6033 | 0.5756 |
| 1.675 | 3.0 | 1587 | 1.6412 | 0.5741 |
| 1.6045 | 4.0 | 2116 | 1.7177 | 0.5717 |
| 1.4962 | 5.0 | 2645 | 1.8518 | 0.5677 |
| 1.4058 | 6.0 | 3174 | 1.9380 | 0.5668 |
| 1.348 | 7.0 | 3703 | 2.0013 | 0.5651 |
| 1.3061 | 8.0 | 4232 | 2.1522 | 0.5629 |
| 1.2537 | 9.0 | 4761 | 2.1630 | 0.5635 |
| 1.208 | 10.0 | 5290 | 2.2419 | 0.5630 |
| 1.1346 | 11.0 | 5819 | 2.2893 | 0.5629 |
| 1.0951 | 12.0 | 6348 | 2.3280 | 0.5639 |
| 1.0306 | 13.0 | 6877 | 2.3896 | 0.5619 |
| 0.9875 | 14.0 | 7406 | 2.3976 | 0.5630 |
| 0.9005 | 15.0 | 7935 | 2.4602 | 0.5610 |
| 0.8609 | 16.0 | 8464 | 2.4857 | 0.5624 |
| 0.7923 | 17.0 | 8993 | 2.4992 | 0.5619 |
| 0.7522 | 18.0 | 9522 | 2.5021 | 0.5613 |
| 0.7038 | 19.0 | 10051 | 2.5203 | 0.5623 |
| 0.6484 | 20.0 | 10580 | 2.5129 | 0.5609 |
Framework versions
- PEFT 0.5.0
- Transformers 4.40.2
- Pytorch 2.3.0
- Datasets 2.19.1
- Tokenizers 0.19.1