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---
license: gemma
library_name: peft
tags:
- alignment-handbook
- trl
- sft
- generated_from_trainer
base_model: google/gemma-2b
datasets:
- llama-duo/synth_classification_dataset_dedup
model-index:
- name: gemma2b-classification-gpt4o-100k
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-classification-gpt4o-100k
This model is a fine-tuned version of [google/gemma-2b](https://huggingface.co/google/gemma-2b) on the llama-duo/synth_classification_dataset_dedup dataset.
It achieves the following results on the evaluation set:
- Loss: 2.8001
## 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: 15
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-------:|:----:|:---------------:|
| 1.4266 | 0.9969 | 159 | 1.9880 |
| 1.3029 | 2.0 | 319 | 1.9710 |
| 1.2414 | 2.9969 | 478 | 1.9794 |
| 1.2012 | 4.0 | 638 | 2.0134 |
| 1.1513 | 4.9969 | 797 | 2.0583 |
| 1.0951 | 6.0 | 957 | 2.1084 |
| 1.0414 | 6.9969 | 1116 | 2.2094 |
| 1.0041 | 8.0 | 1276 | 2.3043 |
| 0.9481 | 8.9969 | 1435 | 2.3989 |
| 0.9006 | 10.0 | 1595 | 2.5173 |
| 0.8626 | 10.9969 | 1754 | 2.6419 |
| 0.8351 | 12.0 | 1914 | 2.7331 |
| 0.8265 | 12.9969 | 2073 | 2.7838 |
| 0.8167 | 14.0 | 2233 | 2.7990 |
| 0.8075 | 14.9530 | 2385 | 2.8001 |
### Framework versions
- PEFT 0.11.1
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1 |