metadata
license: llama2
base_model: meta-llama/Llama-2-7b-hf
tags:
- generated_from_trainer
datasets:
- tyzhu/lmind_hotpot_train8000_eval7405_v1_doc_qa
metrics:
- accuracy
model-index:
- name: lmind_hotpot_train8000_eval7405_v1_doc_qa_meta-llama_Llama-2-7b-hf_lora2
results:
- task:
name: Causal Language Modeling
type: text-generation
dataset:
name: tyzhu/lmind_hotpot_train8000_eval7405_v1_doc_qa
type: tyzhu/lmind_hotpot_train8000_eval7405_v1_doc_qa
metrics:
- name: Accuracy
type: accuracy
value: 0.5864303797468354
lmind_hotpot_train8000_eval7405_v1_doc_qa_meta-llama_Llama-2-7b-hf_lora2
This model is a fine-tuned version of meta-llama/Llama-2-7b-hf on the tyzhu/lmind_hotpot_train8000_eval7405_v1_doc_qa dataset. It achieves the following results on the evaluation set:
- Loss: 2.6271
- Accuracy: 0.5864
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: 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: 10.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.2059 | 1.0 | 1089 | 1.8322 | 0.5952 |
| 1.1499 | 2.0 | 2178 | 1.8031 | 0.5991 |
| 1.0513 | 3.0 | 3267 | 1.8166 | 0.5990 |
| 0.9607 | 4.0 | 4357 | 1.8648 | 0.5974 |
| 0.8735 | 5.0 | 5446 | 1.9525 | 0.5954 |
| 0.7726 | 6.0 | 6535 | 2.0443 | 0.5936 |
| 0.6882 | 7.0 | 7624 | 2.2087 | 0.5896 |
| 0.6014 | 8.0 | 8714 | 2.3552 | 0.5881 |
| 0.5276 | 9.0 | 9803 | 2.4434 | 0.5878 |
| 0.475 | 10.0 | 10890 | 2.6271 | 0.5864 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.14.1