|
--- |
|
license: gemma |
|
library_name: peft |
|
tags: |
|
- alignment-handbook |
|
- trl |
|
- sft |
|
- generated_from_trainer |
|
base_model: google/gemma-2b |
|
datasets: |
|
- llama-duo/synth_summarize_dataset_dedup |
|
model-index: |
|
- name: gemma2b-summarize-gpt4o-2k |
|
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-summarize-gpt4o-2k |
|
|
|
This model is a fine-tuned version of [google/gemma-2b](https://huggingface.co/google/gemma-2b) on the llama-duo/synth_summarize_dataset_dedup dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 2.5878 |
|
|
|
## 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: 8 |
|
- seed: 42 |
|
- distributed_type: multi-GPU |
|
- num_devices: 3 |
|
- gradient_accumulation_steps: 2 |
|
- total_train_batch_size: 48 |
|
- total_eval_batch_size: 24 |
|
- 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 | |
|
|:-------------:|:-----:|:----:|:---------------:| |
|
| 2.9978 | 1.0 | 5 | 3.1071 | |
|
| 2.5123 | 2.0 | 10 | 2.8503 | |
|
| 2.2077 | 3.0 | 15 | 2.7154 | |
|
| 1.9749 | 4.0 | 20 | 2.6507 | |
|
| 1.8015 | 5.0 | 25 | 2.6242 | |
|
| 1.6817 | 6.0 | 30 | 2.6105 | |
|
| 1.6095 | 7.0 | 35 | 2.6003 | |
|
| 1.5701 | 8.0 | 40 | 2.5917 | |
|
| 1.5524 | 9.0 | 45 | 2.5882 | |
|
| 1.5443 | 10.0 | 50 | 2.5878 | |
|
|
|
|
|
### Framework versions |
|
|
|
- PEFT 0.11.1 |
|
- Transformers 4.41.2 |
|
- Pytorch 2.3.0+cu121 |
|
- Datasets 2.19.2 |
|
- Tokenizers 0.19.1 |