Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use autoevaluate/multi-class-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use autoevaluate/multi-class-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="autoevaluate/multi-class-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("autoevaluate/multi-class-classification") model = AutoModelForSequenceClassification.from_pretrained("autoevaluate/multi-class-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| license: apache-2.0 | |
| tags: | |
| - generated_from_trainer | |
| datasets: | |
| - emotion | |
| metrics: | |
| - accuracy | |
| model-index: | |
| - name: autoevaluate/multi-class-classification | |
| results: | |
| - task: | |
| type: text-classification | |
| name: Text Classification | |
| dataset: | |
| name: emotion | |
| type: emotion | |
| config: default | |
| split: test | |
| metrics: | |
| - type: accuracy | |
| value: 0.9185 | |
| name: Accuracy | |
| verified: true | |
| verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZDNlY2I5ZTZkOTBmMTQwMjA0ZTFhYzE4NTdiZGIzYmNiOTkyMjBjMDY0MDJhNGY4ZTBiMGJiZjdhNzk3ODFkZCIsInZlcnNpb24iOjF9.JQbXPplJfzTCXHZrnbQLcSKZJrxvqYQh-BlpYlVMsWL6SSAKAlCb7Srqeoxr6u7byLm7QtufHYUKda7b1dKECw | |
| - type: f1 | |
| value: 0.8692821860210945 | |
| name: F1 Macro | |
| verified: true | |
| verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNTU0YzdlZWJlYjM0MzIyZTMzZWJhZjIzZWVhMzc2NmJkMGJlNTU4YzJjOTQ1NjU5OTI3OGNiZDhhZDE1ZWFhYyIsInZlcnNpb24iOjF9.KxhL3gFTS8RpZNVwLbRzig_xLowmnCOjlMnwIP45Dyq62KafQk4ID3-lTH5J7tf0vRx10wICBSMBARDERy9vAw | |
| - type: f1 | |
| value: 0.9185 | |
| name: F1 Micro | |
| verified: true | |
| verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZTM0OTVlOTE2OGRjODllOWE5MGYzYWIwODhjZjVhNWRjNDQwMmFiMTA3ODNmMzE3NGJmOGU5YmNjMmY0ZWMyNyIsInZlcnNpb24iOjF9.1k1PYE543xvSrIKxGX053X78iZigwvhs8skFlTmC2gfNkPs0dKW7gtf8Xzk-V9yZHnjUkiyu4H_ZnU2WwdNtAg | |
| - type: f1 | |
| value: 0.9181177508591364 | |
| name: F1 Weighted | |
| verified: true | |
| verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZjQxYmFhMzQ1NmM4OTQxYzg5MGYyZDgyNDgzYzQ4ZTY4ZWRmYWNlOTQyNjk3MTljMTdlNzc0YzI1YmEwZGQ5YyIsInZlcnNpb24iOjF9.tFzvcpez6mjSFyWZlgk1_9c_QyasGvQ_hXCTUqzMUdiO7Pof465IBmbKCqPDnEweTcypa1jD4ecvcoPzx-G0BA | |
| - type: precision | |
| value: 0.8738350796775306 | |
| name: Precision Macro | |
| verified: true | |
| verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNTdhMDg2NmU3NDJlNWYwODFiNWZjOWU4NWM5NDc1NjEzMjQ0NjUxZjY1ZDM1OTQ1NzU4YTMyNTA3NTFhMWFlNiIsInZlcnNpb24iOjF9.RVUwjBs1FYBweEboY_kTcCssf3rVLbtQIjZnCQmhBJnCbYyZW6KTCKbt3qiw-FyzjX5P-fkK2GbwpTkipwhGDA | |
| - type: precision | |
| value: 0.9185 | |
| name: Precision Micro | |
| verified: true | |
| verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNjJlOTJmMjA5MGEwODAwMjVkMTMzMWIyNmZlOThlMDc3MmRmYWM5YzI4MTI0Y2E5MDEyMTdkMGYzOGRmMjRhMiIsInZlcnNpb24iOjF9.ttqgrykUq1R10Plm1Tqiol_kYaOTZnyKPEJaqE6l58OT7kyjgmgk2XpdU1f_ZaK9Fvj7IYfy8ew9vJPZ3fc7Aw | |
| - type: precision | |
| value: 0.9179425177997311 | |
| name: Precision Weighted | |
| verified: true | |
| verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNmM5MjlmMmUwZWM3NjAzZjI0NDhkMTY2NTY0NmJkMWNmYzU2MTA5NTlhZmU0OTI2N2MzZTdhYzU0YTVmMmYyOCIsInZlcnNpb24iOjF9.sOOwCp7-K68hCODiHT50Q4iUlEp_QMp13ZPOVK0B7uvePYIUEenp3BERuda-aiK0tJwaSuq428j83mC8EdqsCQ | |
| - type: recall | |
| value: 0.8650962919021573 | |
| name: Recall Macro | |
| verified: true | |
| verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMzlhNmNjZjcyOGM4MmRmN2IxZDExYmFjNzYzYzY4ODMwNmFjNDhjMDVmZmYwZjkzMzQ3ZjgzNmUyODk1YTUyYyIsInZlcnNpb24iOjF9.MkiPaQI1_TjuuPto3KwXhlT3u2wwgO6fg1w_EPV2T74PwdiRsVt11alXTJXgq8hmanrBYnWypk5VzC9OmXZXCw | |
| - type: recall | |
| value: 0.9185 | |
| name: Recall Micro | |
| verified: true | |
| verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMzg0OTQwZWNiMGE2YjA5NThjYTRhMjE5NTNmMmMwNzY0NTY5YWRlZTVhMjZhYmYwOWFiNmQ1YzQxY2E1ZDVmMSIsInZlcnNpb24iOjF9.LM2xWXrJAJdgLJ7HyUH45bkDmB2NrNeX1HSffw5igtoMd7DFsdVrvNEDDfePiW2YQPlA1tZsxDq9Evsj38erBw | |
| - type: recall | |
| value: 0.9185 | |
| name: Recall Weighted | |
| verified: true | |
| verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiYzU3NGU0OTIxZjIwMzc3ODM4YzFiYjEwMjFlNDI4MmU3NDI5NDQwZjNlYzU3ZmNjZDVkNDdjMWIzZjBjZjdiNiIsInZlcnNpb24iOjF9.oza0-N-cJ1nwb2NhFAHqXIpfBLKPOWNJT8yyhrYscxgx_FKCRhv5Czl1HCgOd9pkWceBpVwsgxMCYiVEpQoMAw | |
| - type: loss | |
| value: 0.20907790958881378 | |
| name: loss | |
| verified: true | |
| verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZGRiMzI4MDlhYTYwNWM0Yjk4MjAxNDY0NTEyNGUyOWE5NmFjZGM1YWFiMGQ0Yjg1YmVjZDVjY2EyMzBmZGI0YSIsInZlcnNpb24iOjF9.37MscN7wz25jU_rcAEK33oRAJl_jc-zRRCTn9acgxL6kCf__bV_YpvrvDdnT2ArAVv9m3DyRIOpwYFkDj4EUBQ | |
| - type: matthews_correlation | |
| value: 0.8920254536671932 | |
| name: matthews_correlation | |
| verified: true | |
| verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMDI5MmU2ZjIxZjU0NDU1NDRhMzg1ODI5OGRiOWQ1NGY4YTNjM2JkYTA4ZTY1OTdiMmE2NzFlZTg2NmQyYmRhNSIsInZlcnNpb24iOjF9.jvK80B05dMGBklqPq0Kj4wgn8uJnBtVtUiJfGFpZueV_HJMRoOzwEpXFvYJCA4n04mzFrbr8prDMppQuKm7PBQ | |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You | |
| should probably proofread and complete it, then remove this comment. --> | |
| # multi-class-classification | |
| This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the emotion dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.2009 | |
| - Accuracy: 0.928 | |
| ## 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 | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| | |
| | 0.2643 | 1.0 | 1000 | 0.2009 | 0.928 | | |
| ### Framework versions | |
| - Transformers 4.19.2 | |
| - Pytorch 1.11.0+cu113 | |
| - Datasets 2.2.2 | |
| - Tokenizers 0.12.1 | |