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---
base_model: google/gemma-2-2b-it
datasets:
- GaetanMichelet/chat-60_ft_task-2_auto
- GaetanMichelet/chat-120_ft_task-2_auto
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_auto
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_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-2_auto and the GaetanMichelet/chat-120_ft_task-2_auto datasets.
It achieves the following results on the evaluation set:
- Loss: 0.6387
## 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 |
|:-------------:|:-------:|:----:|:---------------:|
| 1.0219 | 0.9091 | 5 | 1.0249 |
| 0.9649 | 2.0 | 11 | 0.8980 |
| 0.7596 | 2.9091 | 16 | 0.8028 |
| 0.6873 | 4.0 | 22 | 0.7306 |
| 0.6361 | 4.9091 | 27 | 0.6907 |
| 0.5688 | 6.0 | 33 | 0.6625 |
| 0.5268 | 6.9091 | 38 | 0.6464 |
| 0.4821 | 8.0 | 44 | 0.6387 |
| 0.439 | 8.9091 | 49 | 0.6490 |
| 0.3766 | 10.0 | 55 | 0.6785 |
| 0.3045 | 10.9091 | 60 | 0.7300 |
| 0.2261 | 12.0 | 66 | 0.8326 |
| 0.1684 | 12.9091 | 71 | 0.9590 |
| 0.097 | 14.0 | 77 | 1.1236 |
| 0.0478 | 14.9091 | 82 | 1.2809 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.1.2+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1 |