本モデルはaxolotlの使い方の解説記事のデモで作成されたモデルです。モデルとしては特に特に利用価値のないものになっているのでご注意ください。
以下、自動生成されたREADMEです。
gemma-2-2b-axolotl-sft-v1.0
This model is a fine-tuned version of google/gemma-2-2b on the kanhatakeyama/ramdom-to-fixed-multiturn-Calm3, the llm-jp/magpie-sft-v1.0 and the Aratako/magpie-qwen2.5-32b-reasoning-100k-formatted datasets. It achieves the following results on the evaluation set:
- Loss: 1.3378
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: 0.0003
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 16
- total_train_batch_size: 32
- total_eval_batch_size: 2
- optimizer: Use OptimizerNames.PAGED_ADAMW_8BIT with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.3251 | 0.3726 | 50 | 1.3855 |
| 1.3015 | 0.7452 | 100 | 1.3378 |
Framework versions
- PEFT 0.14.0
- Transformers 4.46.3
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3
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