|
--- |
|
library_name: transformers |
|
license: llama3 |
|
base_model: meta-llama/Meta-Llama-3-8B-Instruct |
|
tags: |
|
- llama-factory |
|
- full |
|
- generated_from_trainer |
|
model-index: |
|
- name: sft_full |
|
results: [] |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# sft_full |
|
|
|
This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) on the healthcaremagic dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 1.7460 |
|
|
|
## 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: 1e-05 |
|
- train_batch_size: 8 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- distributed_type: multi-GPU |
|
- num_devices: 8 |
|
- gradient_accumulation_steps: 8 |
|
- total_train_batch_size: 512 |
|
- total_eval_batch_size: 64 |
|
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
|
- lr_scheduler_type: cosine |
|
- lr_scheduler_warmup_ratio: 0.05 |
|
- num_epochs: 3.0 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | |
|
|:-------------:|:------:|:----:|:---------------:| |
|
| 1.2093 | 2.8429 | 500 | 1.7462 | |
|
|
|
### Evaluation results |
|
| Name | Checkpoint | Rouge1 | RougeL | Meteor | Bert Score | |
|
|-------------------------|------------------------------------------------------------------------------------------------------------------|---------|--------|--------|------------| |
|
| baseline instruct model | [Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) | 0.254 | 0.128 | 0.222 | 0.747 | |
|
| full fientune from inst | [sft_llama3_instruct_full](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) | 0.315 | 0.189 | 0.238 | 0.782 | |
|
| lora sft from inst | [sft_llama3_instruct_lora_all](https://huggingface.co/geshijoker/HealthCareMagic_sft_llama3_instruct_lora_all) | 0.271 | 0.143 | 0.194 | 0.774 | |
|
| lora sft from base | [sft_llama3_lora_all](geshijoker/HealthCareMagic_sft_llama3_lora_all) | 0.239 | 0.113 | 0.211 | 0.735 | |
|
| qlora sft from inst | [sft_llama3_instruct_qlora_all](https://huggingface.co/geshijoker/HealthCareMagic_sft_llama3_instruct_qlora_all) | 0.137 | 0.071 | 0.102 | 0.679 | |
|
| qlora sft from base | [sft_llama3_qlora_all ](https://huggingface.co/geshijoker/HealthCareMagic_sft_llama3_qlora_all) | 0.192 | 0.090 | 0.159 | 0.718 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.46.1 |
|
- Pytorch 2.5.1 |
|
- Datasets 3.1.0 |
|
- Tokenizers 0.20.3 |
|
|
