Text Classification
Transformers
TensorBoard
Safetensors
xlm-roberta
sentiment
multilingual
modernbert
sentiment-analysis
product-reviews
place-reviews
text-embeddings-inference
Instructions to use clapAI/roberta-large-multilingual-sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use clapAI/roberta-large-multilingual-sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="clapAI/roberta-large-multilingual-sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("clapAI/roberta-large-multilingual-sentiment") model = AutoModelForSequenceClassification.from_pretrained("clapAI/roberta-large-multilingual-sentiment", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download all_results.json from clapAI/roberta-large-multilingual-sentiment: direct link, hf CLI and curl.
- Browser
- Download file 677 Bytes
-
https://huggingface.co/clapAI/roberta-large-multilingual-sentiment/resolve/main/all_results.json
- Command line
-
hf download hf://clapAI/roberta-large-multilingual-sentiment/all_results.json
-
curl -L -o all_results.json https://huggingface.co/clapAI/roberta-large-multilingual-sentiment/resolve/main/all_results.json
677 Bytes
| { | |
| "epoch": 5.0, | |
| "eval_f1": 0.8249050225524125, | |
| "eval_loss": 0.41357421875, | |
| "eval_precision": 0.825624581488519, | |
| "eval_recall": 0.8243496742948847, | |
| "eval_runtime": 1162.682, | |
| "eval_samples_per_second": 338.386, | |
| "eval_steps_per_second": 0.661, | |
| "test_f1": 0.8262945499829749, | |
| "test_loss": 0.411376953125, | |
| "test_precision": 0.8271664012247752, | |
| "test_recall": 0.8256432203503072, | |
| "test_runtime": 1038.4953, | |
| "test_samples_per_second": 378.852, | |
| "test_steps_per_second": 0.74, | |
| "train_loss": 0.7460857761162166, | |
| "train_runtime": 176390.3873, | |
| "train_samples_per_second": 89.219, | |
| "train_steps_per_second": 0.087 | |
| } |