|
--- |
|
library_name: peft |
|
tags: |
|
- alignment-handbook |
|
- generated_from_trainer |
|
datasets: |
|
- llama-duo/synth_summarize_dataset_dedup |
|
base_model: google/gemma-7b |
|
model-index: |
|
- name: gemma7b-summarize-gemini1_5flash-256k |
|
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. --> |
|
|
|
# gemma7b-summarize-gemini1_5flash-256k |
|
|
|
This model is a fine-tuned version of [google/gemma-7b](https://huggingface.co/google/gemma-7b) on the llama-duo/synth_summarize_dataset_dedup dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 2.4690 |
|
|
|
## 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: 0.0002 |
|
- train_batch_size: 4 |
|
- eval_batch_size: 2 |
|
- seed: 42 |
|
- distributed_type: multi-GPU |
|
- num_devices: 8 |
|
- gradient_accumulation_steps: 2 |
|
- total_train_batch_size: 64 |
|
- total_eval_batch_size: 16 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: cosine |
|
- lr_scheduler_warmup_ratio: 0.1 |
|
- num_epochs: 10 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | |
|
|:-------------:|:------:|:----:|:---------------:| |
|
| 0.9973 | 0.9988 | 414 | 2.5221 | |
|
| 0.9036 | 2.0 | 829 | 2.4358 | |
|
| 0.7651 | 2.9988 | 1243 | 2.3987 | |
|
| 0.7192 | 4.0 | 1658 | 2.3970 | |
|
| 0.6986 | 4.9988 | 2072 | 2.4163 | |
|
| 0.6737 | 6.0 | 2487 | 2.4236 | |
|
| 0.6633 | 6.9988 | 2901 | 2.4494 | |
|
| 0.661 | 8.0 | 3316 | 2.4621 | |
|
| 0.643 | 8.9988 | 3730 | 2.4791 | |
|
| 0.6511 | 9.9879 | 4140 | 2.4690 | |
|
|
|
|
|
### Framework versions |
|
|
|
- PEFT 0.10.0 |
|
- Transformers 4.40.0 |
|
- Pytorch 2.1.2+cu121 |
|
- Datasets 2.18.0 |
|
- Tokenizers 0.19.1 |
