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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-2b-MultiCap
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-2b-MultiCap
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: 0.5983
## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.03
- training_steps: 600
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.8045 | 0.0564 | 50 | 0.8067 |
| 0.7271 | 0.1128 | 100 | 0.6777 |
| 0.688 | 0.1692 | 150 | 0.6309 |
| 0.6268 | 0.2256 | 200 | 0.6176 |
| 0.572 | 0.2820 | 250 | 0.6118 |
| 0.5864 | 0.3384 | 300 | 0.6065 |
| 0.5528 | 0.3948 | 350 | 0.6030 |
| 0.5396 | 0.4512 | 400 | 0.6015 |
| 0.5726 | 0.5076 | 450 | 0.6005 |
| 0.5655 | 0.5640 | 500 | 0.5997 |
| 0.5712 | 0.6204 | 550 | 0.5988 |
| 0.5213 | 0.6768 | 600 | 0.5983 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.44.2
- Pytorch 2.4.0+cu124
- Datasets 2.21.0
- Tokenizers 0.19.1 |