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---
license: llama2
base_model: meta-llama/Llama-2-7b-hf
tags:
- generated_from_trainer
datasets:
- tyzhu/lmind_nq_train6000_eval6489_v1_qa
metrics:
- accuracy
model-index:
- name: lmind_nq_train6000_eval6489_v1_qa_3e-5_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: 0.5965641025641025
---
<!-- 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_3e-5_lora2
This model is a fine-tuned version of [meta-llama/Llama-2-7b-hf](https://huggingface.co/meta-llama/Llama-2-7b-hf) on the tyzhu/lmind_nq_train6000_eval6489_v1_qa dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4443
- Accuracy: 0.5966
## 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: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 4
- 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: 50.0
### Training results
| Training Loss | Epoch | Step | Accuracy | Validation Loss |
|:-------------:|:-----:|:----:|:--------:|:---------------:|
| 2.0369 | 1.0 | 187 | 0.6128 | 1.2953 |
| 1.2821 | 2.0 | 375 | 0.6146 | 1.2741 |
| 1.1987 | 3.0 | 562 | 0.6162 | 1.2715 |
| 1.066 | 4.0 | 750 | 0.6151 | 1.3011 |
| 0.9381 | 5.0 | 937 | 0.6126 | 1.3728 |
| 0.8238 | 6.0 | 1125 | 0.6091 | 1.4599 |
| 0.7289 | 7.0 | 1312 | 0.6064 | 1.5455 |
| 0.6559 | 8.0 | 1500 | 0.6026 | 1.6359 |
| 0.5733 | 9.0 | 1687 | 0.6006 | 1.7149 |
| 0.5336 | 10.0 | 1875 | 0.5989 | 1.8006 |
| 0.5116 | 11.0 | 2062 | 0.5982 | 1.8851 |
| 0.4934 | 12.0 | 2250 | 0.5982 | 1.9262 |
| 0.4823 | 13.0 | 2437 | 0.5974 | 1.9413 |
| 0.47 | 14.0 | 2625 | 0.5967 | 2.0121 |
| 0.4661 | 15.0 | 2812 | 0.5968 | 2.0250 |
| 0.462 | 16.0 | 3000 | 0.5990 | 1.9805 |
| 0.4357 | 17.0 | 3187 | 0.5976 | 2.0656 |
| 0.4348 | 18.0 | 3375 | 0.5979 | 2.0308 |
| 0.4331 | 19.0 | 3562 | 0.5990 | 2.0629 |
| 0.4341 | 20.0 | 3750 | 0.5983 | 2.0815 |
| 0.434 | 21.0 | 3937 | 0.5968 | 2.1253 |
| 0.4335 | 22.0 | 4125 | 0.5971 | 2.1789 |
| 0.4346 | 23.0 | 4312 | 0.5952 | 2.1455 |
| 0.4326 | 24.0 | 4500 | 0.5971 | 2.1990 |
| 0.4139 | 25.0 | 4687 | 0.5976 | 2.1890 |
| 0.4139 | 26.0 | 4875 | 0.5968 | 2.1939 |
| 0.4162 | 27.0 | 5062 | 0.5965 | 2.2190 |
| 0.4177 | 28.0 | 5250 | 0.5955 | 2.2781 |
| 0.4173 | 29.0 | 5437 | 0.5976 | 2.2681 |
| 0.4187 | 30.0 | 5625 | 0.5959 | 2.2996 |
| 0.4199 | 31.0 | 5812 | 0.5981 | 2.2395 |
| 0.4213 | 32.0 | 6000 | 0.5957 | 2.2991 |
| 0.4015 | 33.0 | 6187 | 0.5952 | 2.3223 |
| 0.4058 | 34.0 | 6375 | 0.5957 | 2.3266 |
| 0.4056 | 35.0 | 6562 | 0.5946 | 2.3779 |
| 0.4078 | 36.0 | 6750 | 0.5951 | 2.3453 |
| 0.4097 | 37.0 | 6937 | 0.5965 | 2.3379 |
| 0.4105 | 38.0 | 7125 | 0.5969 | 2.3624 |
| 0.4116 | 39.0 | 7312 | 0.5962 | 2.3846 |
| 0.4121 | 40.0 | 7500 | 0.5945 | 2.3748 |
| 0.3973 | 41.0 | 7687 | 0.5956 | 2.3797 |
| 0.3985 | 42.0 | 7875 | 0.5967 | 2.3599 |
| 0.4014 | 43.0 | 8062 | 0.5971 | 2.3475 |
| 0.4032 | 44.0 | 8250 | 0.5987 | 2.3937 |
| 0.4028 | 45.0 | 8437 | 0.5967 | 2.3863 |
| 0.4027 | 46.0 | 8625 | 0.5956 | 2.4195 |
| 0.4046 | 47.0 | 8812 | 0.5970 | 2.3832 |
| 0.4067 | 48.0 | 9000 | 0.5973 | 2.3805 |
| 0.3923 | 49.0 | 9187 | 0.5957 | 2.4460 |
| 0.3949 | 49.87 | 9350 | 0.5966 | 2.4443 |
### Framework versions
- Transformers 4.34.0
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.14.1
|