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---
base_model: google/gemma-2-2b-it
datasets:
- GaetanMichelet/chat-60_ft_task-2
library_name: peft
license: gemma
tags:
- alignment-handbook
- trl
- sft
- generated_from_trainer
model-index:
- name: Gemma-2-2B_task-2_60-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_60-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 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8957
## 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 |
|:-------------:|:-------:|:----:|:---------------:|
| 1.2929 | 0.6957 | 2 | 1.3116 |
| 1.3056 | 1.7391 | 5 | 1.2842 |
| 1.2411 | 2.7826 | 8 | 1.1890 |
| 1.1401 | 3.8261 | 11 | 1.1172 |
| 1.0766 | 4.8696 | 14 | 1.0738 |
| 1.024 | 5.9130 | 17 | 1.0270 |
| 0.9524 | 6.9565 | 20 | 0.9851 |
| 0.9285 | 8.0 | 23 | 0.9539 |
| 0.8884 | 8.6957 | 25 | 0.9410 |
| 0.8534 | 9.7391 | 28 | 0.9267 |
| 0.8501 | 10.7826 | 31 | 0.9164 |
| 0.8295 | 11.8261 | 34 | 0.9091 |
| 0.7979 | 12.8696 | 37 | 0.9039 |
| 0.796 | 13.9130 | 40 | 0.9001 |
| 0.7651 | 14.9565 | 43 | 0.8977 |
| 0.769 | 16.0 | 46 | 0.8965 |
| 0.733 | 16.6957 | 48 | 0.8957 |
| 0.743 | 17.7391 | 51 | 0.8961 |
| 0.7346 | 18.7826 | 54 | 0.8963 |
| 0.7113 | 19.8261 | 57 | 0.8982 |
| 0.7027 | 20.8696 | 60 | 0.9012 |
| 0.6939 | 21.9130 | 63 | 0.9043 |
| 0.6772 | 22.9565 | 66 | 0.9081 |
| 0.6706 | 24.0 | 69 | 0.9127 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.1.2+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1 |