|
--- |
|
license: gemma |
|
library_name: peft |
|
tags: |
|
- alignment-handbook |
|
- trl |
|
- sft |
|
- generated_from_trainer |
|
base_model: google/gemma-7b |
|
datasets: |
|
- chansung/no_robots_only_coding |
|
model-index: |
|
- name: gemma-7b-sft-qlora-1 |
|
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. --> |
|
|
|
# gemma-7b-sft-qlora-1 |
|
|
|
This model is a fine-tuned version of [google/gemma-7b](https://huggingface.co/google/gemma-7b) on the chansung/no_robots_only_coding dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 2.1615 |
|
|
|
## 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: 2 |
|
- eval_batch_size: 2 |
|
- seed: 42 |
|
- distributed_type: multi-GPU |
|
- num_devices: 4 |
|
- gradient_accumulation_steps: 2 |
|
- total_train_batch_size: 16 |
|
- total_eval_batch_size: 8 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: cosine |
|
- lr_scheduler_warmup_ratio: 0.1 |
|
- num_epochs: 25 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | |
|
|:-------------:|:-----:|:----:|:---------------:| |
|
| 23.7344 | 0.91 | 5 | 7.9584 | |
|
| 14.6026 | 2.0 | 11 | 6.8289 | |
|
| 10.8118 | 2.91 | 16 | 6.4185 | |
|
| 10.8598 | 4.0 | 22 | 5.1061 | |
|
| 7.9354 | 4.91 | 27 | 1.7011 | |
|
| 2.0354 | 6.0 | 33 | 1.4461 | |
|
| 1.4855 | 6.91 | 38 | 1.3565 | |
|
| 1.326 | 8.0 | 44 | 1.2935 | |
|
| 1.1375 | 8.91 | 49 | 1.2696 | |
|
| 0.9091 | 10.0 | 55 | 1.2716 | |
|
| 0.8111 | 10.91 | 60 | 1.2861 | |
|
| 0.689 | 12.0 | 66 | 1.3148 | |
|
| 0.6341 | 12.91 | 71 | 1.3391 | |
|
| 0.5359 | 14.0 | 77 | 1.4232 | |
|
| 0.4664 | 14.91 | 82 | 1.5107 | |
|
| 0.3951 | 16.0 | 88 | 1.6597 | |
|
| 0.3593 | 16.91 | 93 | 1.9377 | |
|
| 0.2802 | 18.0 | 99 | 1.9024 | |
|
| 0.2613 | 18.91 | 104 | 2.0981 | |
|
| 0.2262 | 20.0 | 110 | 2.1472 | |
|
| 0.2169 | 20.91 | 115 | 2.1633 | |
|
| 0.2232 | 22.0 | 121 | 2.1595 | |
|
| 0.2096 | 22.73 | 125 | 2.1615 | |
|
|
|
|
|
### Framework versions |
|
|
|
- PEFT 0.7.1 |
|
- Transformers 4.39.3 |
|
- Pytorch 2.2.2+cu121 |
|
- Datasets 2.18.0 |
|
- Tokenizers 0.15.2 |
