llama7B_LORA_AFG_32_64_v4
This model is a fine-tuned version of meta-llama/Llama-2-7b-chat-hf on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.9318
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: 16
- eval_batch_size: 16
- seed: 100
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 3.0
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.952 | 1.0 | 125 | 0.9609 |
| 0.9045 | 2.0 | 251 | 0.9335 |
| 0.9073 | 2.99 | 375 | 0.9318 |
Framework versions
- PEFT 0.7.2.dev0
- Transformers 4.38.2
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
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Model tree for Kamyar-zeinalipour/Llama2-7B-Syntax-Instruct
Base model
meta-llama/Llama-2-7b-chat-hf
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-2-7b-chat-hf") model = PeftModel.from_pretrained(base_model, "Kamyar-zeinalipour/Llama2-7B-Syntax-Instruct")