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---
base_model: google/gemma-2-2b-it
datasets:
- GaetanMichelet/chat-60_ft_task-1_auto
- GaetanMichelet/chat-120_ft_task-1_auto
- GaetanMichelet/chat-180_ft_task-1_auto
library_name: peft
license: gemma
tags:
- alignment-handbook
- trl
- sft
- generated_from_trainer
model-index:
- name: Gemma-2-2B_task-1_180-samples_config-2_full_auto
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Gemma-2-2B_task-1_180-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 the GaetanMichelet/chat-60_ft_task-1_auto, the GaetanMichelet/chat-120_ft_task-1_auto and the GaetanMichelet/chat-180_ft_task-1_auto datasets.
It achieves the following results on the evaluation set:
- Loss: 0.9375
## 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 |
|:-------------:|:-------:|:----:|:---------------:|
| 2.2783 | 0.9412 | 8 | 2.2320 |
| 1.8925 | 2.0 | 17 | 1.7374 |
| 1.479 | 2.9412 | 25 | 1.3322 |
| 1.0469 | 4.0 | 34 | 1.0631 |
| 0.962 | 4.9412 | 42 | 0.9939 |
| 0.9343 | 6.0 | 51 | 0.9545 |
| 0.8325 | 6.9412 | 59 | 0.9375 |
| 0.7698 | 8.0 | 68 | 0.9379 |
| 0.6897 | 8.9412 | 76 | 0.9577 |
| 0.5925 | 10.0 | 85 | 1.0182 |
| 0.506 | 10.9412 | 93 | 1.1055 |
| 0.3319 | 12.0 | 102 | 1.2682 |
| 0.2649 | 12.9412 | 110 | 1.4429 |
| 0.2121 | 14.0 | 119 | 1.6486 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.1.2+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1