Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use PabloAMC/sentiment-model-100-samples with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PabloAMC/sentiment-model-100-samples with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="PabloAMC/sentiment-model-100-samples")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("PabloAMC/sentiment-model-100-samples") model = AutoModelForSequenceClassification.from_pretrained("PabloAMC/sentiment-model-100-samples", device_map="auto") - Notebooks
- Google Colab
- Kaggle
|
Download README.md from PabloAMC/sentiment-model-100-samples: direct link, hf CLI and curl.
- Browser
- Download file 1.04 kB
-
https://huggingface.co/PabloAMC/sentiment-model-100-samples/resolve/main/README.md
- Command line
-
hf download hf://PabloAMC/sentiment-model-100-samples/README.md
-
curl -L -o README.md https://huggingface.co/PabloAMC/sentiment-model-100-samples/resolve/main/README.md
1.04 kB
metadata
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: sentiment-model-100-samples
results: []
sentiment-model-100-samples
This model is a fine-tuned version of distilbert-base-uncased 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: 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: 1
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2