lmind_hotpot_train8000_eval7405_v1_recite_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_recite_qa dataset. It achieves the following results on the evaluation set:
- Loss: 1.7506
- Accuracy: 0.6631
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 |
---|---|---|---|---|
1.0606 | 1.0 | 1089 | 0.9943 | 0.7197 |
0.9709 | 2.0 | 2178 | 0.9236 | 0.7259 |
0.8688 | 3.0 | 3267 | 0.8481 | 0.7329 |
0.9838 | 4.0 | 4357 | 0.9606 | 0.7221 |
3.857 | 5.0 | 5446 | 10.4449 | 0.4496 |
0.9367 | 6.0 | 6535 | 0.9551 | 0.7223 |
0.8797 | 7.0 | 7624 | 0.9217 | 0.7259 |
0.9011 | 8.0 | 8714 | 0.9460 | 0.7236 |
0.8435 | 9.0 | 9803 | 0.9380 | 0.7243 |
1.9697 | 10.0 | 10890 | 1.7506 | 0.6631 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.14.1
Model tree for tyzhu/lmind_hotpot_train8000_eval7405_v1_recite_qa_meta-llama_Llama-2-7b-hf_lora2
Base model
meta-llama/Llama-2-7b-hf
Finetuned
this model
Dataset used to train tyzhu/lmind_hotpot_train8000_eval7405_v1_recite_qa_meta-llama_Llama-2-7b-hf_lora2
Evaluation results
- Accuracy on tyzhu/lmind_hotpot_train8000_eval7405_v1_recite_qaself-reported0.663