Text Classification
Transformers
PyTorch
Safetensors
English
roberta
sagemaker
roberta-base
text classification
Eval Results (legacy)
text-embeddings-inference
Instructions to use Jorgeutd/sagemaker-roberta-base-emotion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jorgeutd/sagemaker-roberta-base-emotion with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jorgeutd/sagemaker-roberta-base-emotion")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jorgeutd/sagemaker-roberta-base-emotion") model = AutoModelForSequenceClassification.from_pretrained("Jorgeutd/sagemaker-roberta-base-emotion", device_map="auto") - Notebooks
- Google Colab
- Kaggle
|
Download README.md from Jorgeutd/sagemaker-roberta-base-emotion: direct link, hf CLI and curl.
- Browser
- Download file 5.44 kB
-
https://huggingface.co/Jorgeutd/sagemaker-roberta-base-emotion/resolve/main/README.md
- Command line
-
hf download hf://Jorgeutd/sagemaker-roberta-base-emotion/README.md
-
curl -L -o README.md https://huggingface.co/Jorgeutd/sagemaker-roberta-base-emotion/resolve/main/README.md
5.44 kB
| language: en | |
| license: apache-2.0 | |
| tags: | |
| - sagemaker | |
| - roberta-base | |
| - text classification | |
| datasets: | |
| - emotion | |
| widget: | |
| - text: I am really upset that I have to call up to three times to the number on the | |
| back of my insurance card for my call to be answer | |
| model-index: | |
| - name: sagemaker-roberta-base-emotion | |
| results: | |
| - task: | |
| type: text-classification | |
| name: Multi Class Text Classification | |
| dataset: | |
| name: emotion | |
| type: emotion | |
| metrics: | |
| - type: accuracy | |
| value: 94.1 | |
| name: Validation Accuracy | |
| - type: f1 | |
| value: 94.13 | |
| name: Validation F1 | |
| - task: | |
| type: text-classification | |
| name: Text Classification | |
| dataset: | |
| name: emotion | |
| type: emotion | |
| config: default | |
| split: test | |
| metrics: | |
| - type: accuracy | |
| value: 0.931 | |
| name: Accuracy | |
| verified: true | |
| verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNmM1ZmI0NjZhYjdlMWU4NWUwZmFjODFmMmM5MTlhMmEyMmQwOTk2NjQ5ZDNlYmFlMGEyMTY4Y2JiMTcwM2MwNiIsInZlcnNpb24iOjF9.haDbUk1y7nW1e_ext0s1xKefyOzep-XFa1HEkNQEcNV0cHCSRb-0YFakMf5Iee6q_EWFUS-QYxNkgEBlbw3fCQ | |
| - type: precision | |
| value: 0.8833042147663716 | |
| name: Precision Macro | |
| verified: true | |
| verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNjZkOTQyMzkwYjE1ZWQ5YjJkMTEzNmIyZmFlMjkwY2YxNzA3OWE0ZDk5YjJlOWVhOTU5Nzc4ZTk5Mzg5NDcxOCIsInZlcnNpb24iOjF9._XhknNSsiailHiMr1SH9ki7SRswR_b-embALunoCjhBssh9WERkv0z1xpsbw7ORo0wx7WCslZRdJWaQoXOmgDQ | |
| - type: precision | |
| value: 0.931 | |
| name: Precision Micro | |
| verified: true | |
| verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMGY0MTc0ZDBiYmZlYmFmMTcyYjk5MWM0MTRmYTlhY2U1ODY5NTQzNTQ5YjAzN2U0YjljNDAzZDQ5NDBkZDUwYyIsInZlcnNpb24iOjF9.313HYKetR4S4kjcMvEk9Yj2J-Ox8ZqvVk4FLrF6UmxlXYZ4F3put-89BEOxGl_ScugjjAWhKY1pHLPYpKz9PAA | |
| - type: precision | |
| value: 0.9337002742192515 | |
| name: Precision Weighted | |
| verified: true | |
| verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZjQ1ZDIzNmE3MjljMTk2NTBmNzcyMTEyOTUwZTljYTA2MjIwY2E4ZThkNGVjYjQwNzU3MTcxMzBiYzJkNWIzOSIsInZlcnNpb24iOjF9.6yXKQ9WS9AWdt1jxixtA5O2S1bcPTKQqIOw291Ytam8OI-zdTI2jwltT6JdU4lHdhTi5797zeNldJMCxGPR2DQ | |
| - type: recall | |
| value: 0.9087144572668905 | |
| name: Recall Macro | |
| verified: true | |
| verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNzJhNTFmNGJkYTAxNzRiOWQ4YzQyMGY5NGQxMjBiMmRjZTA5OTM2ZjM0NWY0ZDJiOTIyODQzZTZkMzEzZmY4YSIsInZlcnNpb24iOjF9.Fy1gkGvRiyANGU6nYgc5QbhccqAfb4PjxEk1EkJAIAZJjs-f0hffwUDlJt_6gRY3KKnoU2kKg1XxpWjybRY7BQ | |
| - type: recall | |
| value: 0.931 | |
| name: Recall Micro | |
| verified: true | |
| verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiYTgwYWJmZDAzM2VkOGNjNjY3NjViOTFiMTYyZDc4ZDIzY2VhNTcwMDg3MjdiOTI4Nzc5ODI4N2ExYzY5ODAzMyIsInZlcnNpb24iOjF9.bEW-tZ-5JqkPDDfqkrdvzlzTGEJtYqRACZI1Jv7C8fWkJ8uJj0eQ8TDhcdGGDnFML-q1z3tnkO6PJuK9V2IxAg | |
| - type: recall | |
| value: 0.931 | |
| name: Recall Weighted | |
| verified: true | |
| verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiYTM2ZDk4NDQ2YWIwM2VjNzUxZjQ0YzU4MzViZGMzYzA3YjlhMTI1NjQwOTM3M2U4NGJhNTMxYzllMjRkMzU2NSIsInZlcnNpb24iOjF9.k9yprOWEoB0-k306GyDGF-g4uw3kABLc8iE_3E5ZYfVbo9VHPo61GuSsWJyYJ7_aq6zWbzgfOFEwUeVjcmnaDA | |
| - type: f1 | |
| value: 0.8949974527433656 | |
| name: F1 Macro | |
| verified: true | |
| verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiODg0ZDllYWJkYWZkMWY2NjEzYWIxMWIwMWUyZDhmNWEzM2FmN2E0MWEwOTIyMTM2YTI1MDdmYmRmZWQ5ZmVmNCIsInZlcnNpb24iOjF9.DUD3dfb4vRu-Z9YxvDErJaPLuZIEDBNsdqzkf4ee6dkOCOnYtUhGAybnxtGN1xSYsynXYhU-ymCajWcrVKUCAA | |
| - type: f1 | |
| value: 0.931 | |
| name: F1 Micro | |
| verified: true | |
| verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiOGU0MTYyOTNjOTBmNzAxNjVlZmQxYmRkMmE5MWY2NzhlNjg0ZGZkMmNmZmI3Zjk1NjJlYTdjMGRhMDMwYzAzNCIsInZlcnNpb24iOjF9.h0wCmhwRT4qRZJcc2zGP3T7dF0_wKdKzTtSVoVWFOUzQZ3RoeY2Hfjl3XA7yyw9KnoDWnLiW8DU_5kOBX-peCQ | |
| - type: f1 | |
| value: 0.9318434300647934 | |
| name: F1 Weighted | |
| verified: true | |
| verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZmU4OGY4M2NkYWExNjI3Yjk0YmYzNWJjZGQ5ZGNmYzc4ZDk4YzRmZDRiNmRkN2VlNDZhOGIwZDc3MzcxYjVlYiIsInZlcnNpb24iOjF9.qhwi7AV-7NSm1yVd8v1Ea3nTRAFXfqLMwUJ5PUbPSa11jJ0tZNOQVDXHMAD8fVmoueLgZNRUpPVIB881Sq3EBg | |
| - type: loss | |
| value: 0.17379647493362427 | |
| name: loss | |
| verified: true | |
| verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNDdjODE2MjA5ODg2MmM2OWJmMjMzMzUzNGU1ZDc5NjRkNGU4N2VmNmM2NWE0YTEyYWMxNGUzN2M3YTkxNzUyMCIsInZlcnNpb24iOjF9.qcQWfHuRnfiluicR7gke3vm9u701hB4Bp0YaX2opaxL6d5DRCzuqAg-2kdmhhOL-8DW5JhY6gTrF14AEuEE9Cw | |
| ## roberta-base | |
| This model is a fine-tuned model that was trained using Amazon SageMaker and the new Hugging Face Deep Learning container. | |
| - Problem type: Multi Class Text Classification (emotion detection). | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.1613253802061081 | |
| - f1: 0.9413321705151999 | |
| ## Hyperparameters | |
| ```json | |
| { | |
| "epochs": 10, | |
| "train_batch_size": 16, | |
| "learning_rate": 3e-5, | |
| "weight_decay":0.01, | |
| "load_best_model_at_end": true, | |
| "model_name":"roberta-base", | |
| "do_eval": True, | |
| "load_best_model_at_end":True | |
| } | |
| ``` | |
| ## Validation Metrics | |
| | key | value | | |
| | --- | ----- | | |
| | eval_accuracy | 0.941 | | |
| | eval_f1 | 0.9413321705151999 | | |
| | eval_loss | 0.1613253802061081| | |
| | eval_recall | 0.941 | | |
| | eval_precision | 0.9419519436781406 | | |