metadata
license: llama2
base_model: meta-llama/Llama-2-7b-hf
tags:
- generated_from_trainer
datasets:
- tyzhu/lmind_nq_train6000_eval6489_v1_doc_qa_v3
metrics:
- accuracy
model-index:
- name: >-
lmind_nq_train6000_eval6489_v1_doc_qa_v3_meta-llama_Llama-2-7b-hf_3e-5_lora2
results:
- task:
name: Causal Language Modeling
type: text-generation
dataset:
name: tyzhu/lmind_nq_train6000_eval6489_v1_doc_qa_v3
type: tyzhu/lmind_nq_train6000_eval6489_v1_doc_qa_v3
metrics:
- name: Accuracy
type: accuracy
value: 0.5965641025641025
lmind_nq_train6000_eval6489_v1_doc_qa_v3_meta-llama_Llama-2-7b-hf_3e-5_lora2
This model is a fine-tuned version of meta-llama/Llama-2-7b-hf on the tyzhu/lmind_nq_train6000_eval6489_v1_doc_qa_v3 dataset. It achieves the following results on the evaluation set:
- Loss: 2.0825
- 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: 20.0
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
1.3948 | 1.0 | 529 | 1.3087 | 0.6132 |
1.3789 | 2.0 | 1058 | 1.2897 | 0.6146 |
1.3259 | 3.0 | 1587 | 1.2849 | 0.6179 |
1.2853 | 4.0 | 2116 | 1.3169 | 0.6159 |
1.2556 | 5.0 | 2645 | 1.3532 | 0.6132 |
1.1972 | 6.0 | 3174 | 1.4135 | 0.6126 |
1.1839 | 7.0 | 3703 | 1.5007 | 0.6081 |
1.1334 | 8.0 | 4232 | 1.5242 | 0.6074 |
1.0966 | 9.0 | 4761 | 1.6107 | 0.5803 |
1.0485 | 10.0 | 5290 | 1.6749 | 0.6049 |
1.021 | 11.0 | 5819 | 1.7324 | 0.6015 |
0.9918 | 12.0 | 6348 | 1.7632 | 0.6007 |
0.947 | 13.0 | 6877 | 1.8303 | 0.6011 |
0.9376 | 14.0 | 7406 | 1.8873 | 0.5991 |
0.898 | 15.0 | 7935 | 1.9688 | 0.5976 |
0.8559 | 16.0 | 8464 | 1.9724 | 0.5988 |
0.8348 | 17.0 | 8993 | 1.9815 | 0.5714 |
0.8106 | 18.0 | 9522 | 2.0386 | 0.598 |
0.7848 | 19.0 | 10051 | 2.0627 | 0.5964 |
0.745 | 20.0 | 10580 | 2.0825 | 0.5966 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.14.1