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---
base_model: google/gemma-2-2b-it
datasets:
- GaetanMichelet/chat-60_ft_task-3
- GaetanMichelet/chat-120_ft_task-3
- GaetanMichelet/chat-180_ft_task-3
library_name: peft
license: gemma
tags:
- alignment-handbook
- trl
- sft
- generated_from_trainer
model-index:
- name: Gemma-2-2B_task-3_180-samples_config-2
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_180-samples_config-2
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-3, the GaetanMichelet/chat-120_ft_task-3 and the GaetanMichelet/chat-180_ft_task-3 datasets.
It achieves the following results on the evaluation set:
- Loss: 0.4529
## 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 |
|:-------------:|:-------:|:----:|:---------------:|
| 3.2784 | 0.9412 | 8 | 3.0451 |
| 1.6125 | 2.0 | 17 | 1.3316 |
| 0.7031 | 2.9412 | 25 | 0.6673 |
| 0.3776 | 4.0 | 34 | 0.5516 |
| 0.3705 | 4.9412 | 42 | 0.4893 |
| 0.4428 | 6.0 | 51 | 0.4587 |
| 0.264 | 6.9412 | 59 | 0.4529 |
| 0.2488 | 8.0 | 68 | 0.4680 |
| 0.211 | 8.9412 | 76 | 0.4985 |
| 0.1326 | 10.0 | 85 | 0.5514 |
| 0.1028 | 10.9412 | 93 | 0.6646 |
| 0.0306 | 12.0 | 102 | 0.8112 |
| 0.0188 | 12.9412 | 110 | 0.9622 |
| 0.0227 | 14.0 | 119 | 0.9967 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.1.2+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1 |