|
--- |
|
license: gemma |
|
library_name: peft |
|
tags: |
|
- alignment-handbook |
|
- trl |
|
- sft |
|
- generated_from_trainer |
|
base_model: google/gemma-1.1-2b-it |
|
datasets: |
|
- llama-duo/synth_summarize_dataset_dedup |
|
model-index: |
|
- name: gemma2b-it-1.1-summarize-gpt4o-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. --> |
|
|
|
# gemma2b-it-1.1-summarize-gpt4o-256k |
|
|
|
This model is a fine-tuned version of [google/gemma-1.1-2b-it](https://huggingface.co/google/gemma-1.1-2b-it) on the llama-duo/synth_summarize_dataset_dedup dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 2.7127 |
|
|
|
## 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: 8 |
|
- eval_batch_size: 4 |
|
- seed: 42 |
|
- distributed_type: multi-GPU |
|
- num_devices: 8 |
|
- gradient_accumulation_steps: 2 |
|
- total_train_batch_size: 128 |
|
- total_eval_batch_size: 32 |
|
- 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 | |
|
|:-------------:|:------:|:----:|:---------------:| |
|
| 0.9633 | 0.9976 | 206 | 2.6959 | |
|
| 0.865 | 2.0 | 413 | 2.6511 | |
|
| 0.8266 | 2.9976 | 619 | 2.6475 | |
|
| 0.7953 | 4.0 | 826 | 2.6603 | |
|
| 0.7708 | 4.9976 | 1032 | 2.6720 | |
|
| 0.75 | 6.0 | 1239 | 2.6898 | |
|
| 0.7446 | 6.9976 | 1445 | 2.7026 | |
|
| 0.7301 | 8.0 | 1652 | 2.7081 | |
|
| 0.7268 | 8.9976 | 1858 | 2.7128 | |
|
| 0.7318 | 9.9758 | 2060 | 2.7127 | |
|
|
|
|
|
### Framework versions |
|
|
|
- PEFT 0.11.1 |
|
- Transformers 4.41.2 |
|
- Pytorch 2.3.1+cu121 |
|
- Datasets 2.19.2 |
|
- Tokenizers 0.19.1 |
