Instructions to use jahb57/test_trainer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jahb57/test_trainer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jahb57/test_trainer")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("jahb57/test_trainer") model = AutoModelForSequenceClassification.from_pretrained("jahb57/test_trainer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from jahb57/test_trainer: direct link, hf CLI and curl.
- Browser
- Download file 1.76 kB
-
https://huggingface.co/jahb57/test_trainer/resolve/main/README.md
- Command line
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hf download hf://jahb57/test_trainer/README.md
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curl -L -o README.md https://huggingface.co/jahb57/test_trainer/resolve/main/README.md
1.76 kB
| license: mit | |
| base_model: gpt2 | |
| tags: | |
| - generated_from_trainer | |
| datasets: | |
| - yelp_review_full | |
| metrics: | |
| - accuracy | |
| model-index: | |
| - name: test_trainer | |
| results: | |
| - task: | |
| name: Text Classification | |
| type: text-classification | |
| dataset: | |
| name: yelp_review_full | |
| type: yelp_review_full | |
| config: yelp_review_full | |
| split: test | |
| args: yelp_review_full | |
| metrics: | |
| - name: Accuracy | |
| type: accuracy | |
| value: 0.584 | |
| <!-- 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. --> | |
| # test_trainer | |
| This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the yelp_review_full dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 1.0617 | |
| - Accuracy: 0.584 | |
| ## 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: 4 | |
| - eval_batch_size: 4 | |
| - seed: 42 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: linear | |
| - num_epochs: 3.0 | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| | |
| | No log | 1.0 | 250 | 1.1204 | 0.515 | | |
| | 1.2411 | 2.0 | 500 | 1.0231 | 0.57 | | |
| | 1.2411 | 3.0 | 750 | 1.0617 | 0.584 | | |
| ### Framework versions | |
| - Transformers 4.34.1 | |
| - Pytorch 2.1.0+cu118 | |
| - Datasets 2.14.6 | |
| - Tokenizers 0.14.1 | |