Text Classification
Transformers
PyTorch
TensorBoard
English
roberta
depression
reddit
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use mrjunos/depression-reddit-distilroberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mrjunos/depression-reddit-distilroberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mrjunos/depression-reddit-distilroberta-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mrjunos/depression-reddit-distilroberta-base") model = AutoModelForSequenceClassification.from_pretrained("mrjunos/depression-reddit-distilroberta-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download train_results.json from mrjunos/depression-reddit-distilroberta-base: direct link, hf CLI and curl.
- Browser
- Download file 204 Bytes
-
https://huggingface.co/mrjunos/depression-reddit-distilroberta-base/resolve/main/train_results.json
- Command line
-
hf download hf://mrjunos/depression-reddit-distilroberta-base/train_results.json
-
curl -L -o train_results.json https://huggingface.co/mrjunos/depression-reddit-distilroberta-base/resolve/main/train_results.json
204 Bytes
| { | |
| "epoch": 3.0, | |
| "total_flos": 1289876456775552.0, | |
| "train_loss": 0.08316168100374328, | |
| "train_runtime": 660.866, | |
| "train_samples_per_second": 28.072, | |
| "train_steps_per_second": 3.509 | |
| } |