Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use SSEF-HG-AC/temp_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SSEF-HG-AC/temp_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SSEF-HG-AC/temp_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SSEF-HG-AC/temp_model") model = AutoModelForSequenceClassification.from_pretrained("SSEF-HG-AC/temp_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from SSEF-HG-AC/temp_model: direct link, hf CLI and curl.
- Browser
- Download file 1.2 kB
-
https://huggingface.co/SSEF-HG-AC/temp_model/resolve/main/README.md
- Command line
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hf download hf://SSEF-HG-AC/temp_model/README.md
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curl -L -o README.md https://huggingface.co/SSEF-HG-AC/temp_model/resolve/main/README.md
1.2 kB
metadata
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: test_model
results: []
test_model
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4058
- Accuracy: 0.7705
- F1: 0.4167
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-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0