|
--- |
|
library_name: transformers |
|
license: other |
|
base_model: clinno/eightwords-20241112 |
|
tags: |
|
- llama-factory |
|
- full |
|
- generated_from_trainer |
|
model-index: |
|
- name: sft |
|
results: [] |
|
datasets: |
|
- clinno/eightwords-241112 |
|
--- |
|
Multi-turn fine-tuning |
|
--- |
|
library_name: transformers |
|
license: other |
|
base_model: clinno/eightwords-20241112 |
|
tags: |
|
- llama-factory |
|
- full |
|
- generated_from_trainer |
|
model-index: |
|
- name: sft |
|
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 |
|
|
|
This model is a fine-tuned version of [clinno/eightwords-20241112](https://huggingface.co/clinno/eightwords-20241112) on the identity and the eightwords-241112 datasets. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.9320 |
|
|
|
## 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: 2 |
|
- eval_batch_size: 1 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 8 |
|
- total_train_batch_size: 16 |
|
- 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: 0.1 |
|
- num_epochs: 16.0 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | |
|
|:-------------:|:-------:|:----:|:---------------:| |
|
| 0.7759 | 4.4608 | 1000 | 1.0107 | |
|
| 0.554 | 8.9215 | 2000 | 0.9391 | |
|
| 0.423 | 13.3845 | 3000 | 0.9251 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.46.1 |
|
- Pytorch 2.5.0+cu121 |
|
- Datasets 3.1.0 |
|
- Tokenizers 0.20.3 |
