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---
base_model: google/gemma-2-2b-it
datasets:
- GaetanMichelet/chat-60_ft_task-2
- GaetanMichelet/chat-120_ft_task-2
library_name: peft
license: gemma
tags:
- alignment-handbook
- trl
- sft
- generated_from_trainer
model-index:
- name: Gemma-2-2B_task-2_120-samples_config-2_full
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-2_120-samples_config-2_full
This model is a fine-tuned version of [google/gemma-2-2b-it](https://huggingface.co./google/gemma-2-2b-it) on the GaetanMichelet/chat-60_ft_task-2 and the GaetanMichelet/chat-120_ft_task-2 datasets.
It achieves the following results on the evaluation set:
- Loss: 0.8742
## 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 |
|:-------------:|:-------:|:----:|:---------------:|
| 1.356 | 0.9091 | 5 | 1.3237 |
| 1.3153 | 2.0 | 11 | 1.2306 |
| 1.1344 | 2.9091 | 16 | 1.1313 |
| 1.0582 | 4.0 | 22 | 1.0518 |
| 0.9757 | 4.9091 | 27 | 0.9752 |
| 0.8903 | 6.0 | 33 | 0.9265 |
| 0.8676 | 6.9091 | 38 | 0.9079 |
| 0.8368 | 8.0 | 44 | 0.8935 |
| 0.8107 | 8.9091 | 49 | 0.8845 |
| 0.8061 | 10.0 | 55 | 0.8781 |
| 0.7712 | 10.9091 | 60 | 0.8747 |
| 0.747 | 12.0 | 66 | 0.8742 |
| 0.7182 | 12.9091 | 71 | 0.8779 |
| 0.7025 | 14.0 | 77 | 0.8851 |
| 0.626 | 14.9091 | 82 | 0.8947 |
| 0.633 | 16.0 | 88 | 0.9076 |
| 0.583 | 16.9091 | 93 | 0.9299 |
| 0.5357 | 18.0 | 99 | 0.9467 |
| 0.5232 | 18.9091 | 104 | 0.9674 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.1.2+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1 |