|
--- |
|
base_model: google/gemma-2-2b-it |
|
library_name: peft |
|
license: gemma |
|
tags: |
|
- trl |
|
- sft |
|
- generated_from_trainer |
|
model-index: |
|
- name: Gemma-2-2B_task-1_60-samples_config-2_auto |
|
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-2-2B_task-1_60-samples_config-2_auto |
|
|
|
This model is a fine-tuned version of [google/gemma-2-2b-it](https://huggingface.co./google/gemma-2-2b-it) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 1.5026 |
|
|
|
## 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: 0.0001 |
|
- train_batch_size: 1 |
|
- eval_batch_size: 1 |
|
- seed: 42 |
|
- distributed_type: multi-GPU |
|
- gradient_accumulation_steps: 16 |
|
- total_train_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: 50 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | |
|
|:-------------:|:-------:|:----:|:---------------:| |
|
| 1.5832 | 0.6957 | 2 | 1.6094 | |
|
| 1.5979 | 1.7391 | 5 | 1.4841 | |
|
| 1.304 | 2.7826 | 8 | 1.1955 | |
|
| 1.1472 | 3.8261 | 11 | 1.0739 | |
|
| 0.925 | 4.8696 | 14 | 1.0285 | |
|
| 0.8884 | 5.9130 | 17 | 1.0012 | |
|
| 0.7766 | 6.9565 | 20 | 0.9815 | |
|
| 0.7111 | 8.0 | 23 | 0.9705 | |
|
| 0.6764 | 8.6957 | 25 | 0.9787 | |
|
| 0.5511 | 9.7391 | 28 | 0.9883 | |
|
| 0.5029 | 10.7826 | 31 | 1.0112 | |
|
| 0.3922 | 11.8261 | 34 | 1.0753 | |
|
| 0.3437 | 12.8696 | 37 | 1.1805 | |
|
| 0.2457 | 13.9130 | 40 | 1.3212 | |
|
| 0.1916 | 14.9565 | 43 | 1.5026 | |
|
|
|
|
|
### Framework versions |
|
|
|
- PEFT 0.12.0 |
|
- Transformers 4.44.0 |
|
- Pytorch 2.1.2+cu121 |
|
- Datasets 2.20.0 |
|
- Tokenizers 0.19.1 |