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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_3e-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: 0.5824050632911393
---
<!-- 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_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_hotpot_train8000_eval7405_v1_qa dataset.
It achieves the following results on the evaluation set:
- Loss: 2.9797
- Accuracy: 0.5824
## 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: 20.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.8255 | 1.0 | 250 | 1.8392 | 0.6054 |
| 1.7368 | 2.0 | 500 | 1.8111 | 0.6078 |
| 1.6689 | 3.0 | 750 | 1.8103 | 0.6075 |
| 1.5555 | 4.0 | 1000 | 1.8414 | 0.6067 |
| 1.4559 | 5.0 | 1250 | 1.8992 | 0.6038 |
| 1.3514 | 6.0 | 1500 | 1.9584 | 0.6018 |
| 1.2491 | 7.0 | 1750 | 2.0300 | 0.6000 |
| 1.1749 | 8.0 | 2000 | 2.1051 | 0.5982 |
| 1.0769 | 9.0 | 2250 | 2.1948 | 0.5954 |
| 1.0134 | 10.0 | 2500 | 2.2515 | 0.5943 |
| 0.9209 | 11.0 | 2750 | 2.3421 | 0.5921 |
| 0.8636 | 12.0 | 3000 | 2.4443 | 0.5905 |
| 0.7866 | 13.0 | 3250 | 2.5574 | 0.588 |
| 0.7448 | 14.0 | 3500 | 2.5800 | 0.5867 |
| 0.6709 | 15.0 | 3750 | 2.6912 | 0.5846 |
| 0.6439 | 16.0 | 4000 | 2.7546 | 0.5853 |
| 0.5869 | 17.0 | 4250 | 2.7997 | 0.5831 |
| 0.5596 | 18.0 | 4500 | 2.8435 | 0.5833 |
| 0.5205 | 19.0 | 4750 | 2.9510 | 0.5833 |
| 0.5045 | 20.0 | 5000 | 2.9797 | 0.5824 |
### Framework versions
- Transformers 4.34.0
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.14.1
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