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---
license: llama2
base_model: meta-llama/Llama-2-7b-hf
tags:
- generated_from_trainer
datasets:
- tyzhu/lmind_hotpot_train8000_eval7405_v1_qa
metrics:
- accuracy
model-index:
- name: lmind_hotpot_train8000_eval7405_v1_qa_5e-5_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: 0.5839240506329114
---
<!-- 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_hotpot_train8000_eval7405_v1_qa_5e-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_hotpot_train8000_eval7405_v1_qa dataset.
It achieves the following results on the evaluation set:
- Loss: 3.2298
- Accuracy: 0.5839
## 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: 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: 20.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.798 | 1.0 | 250 | 1.8213 | 0.6067 |
| 1.7 | 2.0 | 500 | 1.8046 | 0.6077 |
| 1.5869 | 3.0 | 750 | 1.8293 | 0.6071 |
| 1.4349 | 4.0 | 1000 | 1.8974 | 0.6043 |
| 1.3111 | 5.0 | 1250 | 1.9769 | 0.6015 |
| 1.197 | 6.0 | 1500 | 2.0635 | 0.5992 |
| 1.0729 | 7.0 | 1750 | 2.1523 | 0.5975 |
| 0.9833 | 8.0 | 2000 | 2.2640 | 0.5947 |
| 0.8672 | 9.0 | 2250 | 2.3643 | 0.5924 |
| 0.7883 | 10.0 | 2500 | 2.4598 | 0.5908 |
| 0.6879 | 11.0 | 2750 | 2.5669 | 0.5890 |
| 0.6295 | 12.0 | 3000 | 2.7000 | 0.5885 |
| 0.5545 | 13.0 | 3250 | 2.8281 | 0.5851 |
| 0.5208 | 14.0 | 3500 | 2.8794 | 0.5853 |
| 0.4679 | 15.0 | 3750 | 2.9184 | 0.5863 |
| 0.4464 | 16.0 | 4000 | 3.0791 | 0.5852 |
| 0.4136 | 17.0 | 4250 | 3.0832 | 0.5856 |
| 0.4021 | 18.0 | 4500 | 3.0944 | 0.5847 |
| 0.3776 | 19.0 | 4750 | 3.2120 | 0.5828 |
| 0.373 | 20.0 | 5000 | 3.2298 | 0.5839 |
### Framework versions
- Transformers 4.34.0
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.14.1
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