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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-4_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: 0.5813164556962025
---
<!-- 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-4_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: 2.9420
- Accuracy: 0.5813
## 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: 0.0005
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.8732 | 1.0 | 250 | 2.0111 | 0.5939 |
| 1.6142 | 2.0 | 500 | 1.8443 | 0.6051 |
| 1.206 | 3.0 | 750 | 1.9818 | 0.6007 |
| 0.8693 | 4.0 | 1000 | 2.2100 | 0.5941 |
| 0.6023 | 5.0 | 1250 | 2.3756 | 0.5910 |
| 0.4717 | 6.0 | 1500 | 2.5421 | 0.5896 |
| 0.3938 | 7.0 | 1750 | 2.6587 | 0.5891 |
| 0.3697 | 8.0 | 2000 | 2.7532 | 0.5873 |
| 0.3617 | 9.0 | 2250 | 2.7664 | 0.5870 |
| 0.3607 | 10.0 | 2500 | 2.8514 | 0.5867 |
| 0.3414 | 11.0 | 2750 | 2.8932 | 0.5861 |
| 0.3439 | 12.0 | 3000 | 2.9545 | 0.5855 |
| 0.335 | 13.0 | 3250 | 2.8991 | 0.5843 |
| 0.3391 | 14.0 | 3500 | 2.8793 | 0.5840 |
| 0.328 | 15.0 | 3750 | 2.8954 | 0.5851 |
| 0.3351 | 16.0 | 4000 | 2.9140 | 0.5838 |
| 0.3252 | 17.0 | 4250 | 2.9297 | 0.5825 |
| 0.332 | 18.0 | 4500 | 2.9812 | 0.5834 |
| 0.324 | 19.0 | 4750 | 2.9823 | 0.5808 |
| 0.3329 | 20.0 | 5000 | 2.9420 | 0.5813 |
### Framework versions
- Transformers 4.34.0
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.14.1
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