Text Classification
Transformers
PyTorch
Safetensors
Danish
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use vesteinn/danish_sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vesteinn/danish_sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="vesteinn/danish_sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("vesteinn/danish_sentiment") model = AutoModelForSequenceClassification.from_pretrained("vesteinn/danish_sentiment") - Notebooks
- Google Colab
- Kaggle
da_sent_xlm
This model is a fine-tuned version of cardiffnlp/twitter-xlm-roberta-base-sentiment on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.7179
- Accuracy: 0.7657
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: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5.0
Training results
Framework versions
- Transformers 4.24.0.dev0
- Pytorch 1.12.1
- Datasets 2.6.1
- Tokenizers 0.12.1
- Downloads last month
- 11