Instructions to use ksr270894/tmp_trainer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use ksr270894/tmp_trainer with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
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Download README.md from ksr270894/tmp_trainer: direct link, hf CLI and curl.
- Browser
- Download file 1.15 kB
-
https://huggingface.co/ksr270894/tmp_trainer/resolve/main/README.md
- Command line
-
hf download hf://ksr270894/tmp_trainer/README.md
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curl -L -o README.md https://huggingface.co/ksr270894/tmp_trainer/resolve/main/README.md
1.15 kB
metadata
library_name: peft
license: apache-2.0
base_model: HuggingFaceTB/SmolVLM-Base
tags:
- generated_from_trainer
model-index:
- name: tmp_trainer
results: []
tmp_trainer
This model is a fine-tuned version of HuggingFaceTB/SmolVLM-Base on the None dataset.
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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3.0
Framework versions
- PEFT 0.14.0
- Transformers 4.47.1
- Pytorch 2.1.0+cu118
- Datasets 3.2.0
- Tokenizers 0.21.0