license: other | |
base_model: google/gemma-2-9b-it | |
tags: | |
- llama-factory | |
- full | |
- generated_from_trainer | |
model-index: | |
- name: sft | |
results: [] | |
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should probably proofread and complete it, then remove this comment. --> | |
# sft | |
This model is a fine-tuned version of [google/gemma-2-9b-it](https://huggingface.co/google/gemma-2-9b-it) on the tax_qna_data_income_only dataset. | |
It achieves the following results on the evaluation set: | |
- Loss: 1.1982 | |
## 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: 2e-06 | |
- train_batch_size: 1 | |
- eval_batch_size: 1 | |
- seed: 42 | |
- distributed_type: multi-GPU | |
- num_devices: 4 | |
- gradient_accumulation_steps: 8 | |
- total_train_batch_size: 32 | |
- total_eval_batch_size: 4 | |
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
- lr_scheduler_type: cosine | |
- lr_scheduler_warmup_ratio: 0.1 | |
- num_epochs: 1 | |
### Training results | |
### Framework versions | |
- Transformers 4.44.0 | |
- Pytorch 2.2.0a0+81ea7a4 | |
- Datasets 2.21.0 | |
- Tokenizers 0.19.1 | |