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---
license: other
base_model: Qwen/Qwen1.5-4B
tags:
- generated_from_trainer
datasets:
- tyzhu/lmind_nq_train6000_eval6489_v1_qa
metrics:
- accuracy
model-index:
- name: lmind_nq_train6000_eval6489_v1_qa_Qwen_Qwen1.5-4B_lora2
results:
- task:
name: Causal Language Modeling
type: text-generation
dataset:
name: tyzhu/lmind_nq_train6000_eval6489_v1_qa
type: tyzhu/lmind_nq_train6000_eval6489_v1_qa
metrics:
- name: Accuracy
type: accuracy
value: 0.5578974358974359
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_nq_train6000_eval6489_v1_qa_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_nq_train6000_eval6489_v1_qa dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4726
- Accuracy: 0.5579
## 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 |
|:-------------:|:-------:|:----:|:--------:|:---------------:|
| 1.7657 | 0.9973 | 187 | 0.5738 | 1.6215 |
| 1.497 | 2.0 | 375 | 0.5742 | 1.6180 |
| 1.2345 | 2.9973 | 562 | 0.5713 | 1.6951 |
| 1.0084 | 4.0 | 750 | 0.5659 | 1.8059 |
| 0.8397 | 4.9973 | 937 | 0.5647 | 1.9245 |
| 0.7186 | 6.0 | 1125 | 0.5614 | 2.0345 |
| 0.6421 | 6.9973 | 1312 | 0.5608 | 2.1148 |
| 0.5968 | 8.0 | 1500 | 0.5585 | 2.1779 |
| 0.5417 | 8.9973 | 1687 | 0.5568 | 2.2654 |
| 0.5356 | 9.9733 | 1870 | 0.5594 | 2.2527 |
| 0.5261 | 10.9973 | 2057 | 2.3376 | 0.5585 |
| 0.5179 | 12.0 | 2245 | 2.3704 | 0.5595 |
| 0.5116 | 12.9973 | 2432 | 2.3617 | 0.5589 |
| 0.5056 | 14.0 | 2620 | 2.4022 | 0.5581 |
| 0.5063 | 14.9973 | 2807 | 2.3861 | 0.5587 |
| 0.4796 | 16.0 | 2995 | 2.3658 | 0.5585 |
| 0.4757 | 16.9973 | 3182 | 2.4195 | 0.5577 |
| 0.4779 | 18.0 | 3370 | 2.4573 | 0.5573 |
| 0.4782 | 18.9973 | 3557 | 2.4896 | 0.5589 |
| 0.4784 | 19.9733 | 3740 | 2.4726 | 0.5579 |
### 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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