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---
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-3_60-samples_config-2_full_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-3_60-samples_config-2_full_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: 0.9809
## 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 |
|:-------------:|:-------:|:----:|:---------------:|
| 1.3458 | 0.6957 | 2 | 1.3568 |
| 1.3656 | 1.7391 | 5 | 1.3315 |
| 1.3043 | 2.7826 | 8 | 1.2450 |
| 1.2137 | 3.8261 | 11 | 1.1760 |
| 1.1349 | 4.8696 | 14 | 1.1266 |
| 1.0892 | 5.9130 | 17 | 1.0786 |
| 1.0063 | 6.9565 | 20 | 1.0362 |
| 0.9866 | 8.0 | 23 | 1.0086 |
| 0.9437 | 8.6957 | 25 | 0.9958 |
| 0.9105 | 9.7391 | 28 | 0.9805 |
| 0.9086 | 10.7826 | 31 | 0.9711 |
| 0.884 | 11.8261 | 34 | 0.9645 |
| 0.852 | 12.8696 | 37 | 0.9601 |
| 0.8465 | 13.9130 | 40 | 0.9575 |
| 0.8197 | 14.9565 | 43 | 0.9567 |
| 0.8147 | 16.0 | 46 | 0.9571 |
| 0.7741 | 16.6957 | 48 | 0.9576 |
| 0.7843 | 17.7391 | 51 | 0.9597 |
| 0.7714 | 18.7826 | 54 | 0.9630 |
| 0.7444 | 19.8261 | 57 | 0.9685 |
| 0.7328 | 20.8696 | 60 | 0.9758 |
| 0.7226 | 21.9130 | 63 | 0.9809 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.1.2+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1 |