Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use Moeinizadi/BSF-Custom-Emotions-Robust-20260326-0611 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Moeinizadi/BSF-Custom-Emotions-Robust-20260326-0611 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Moeinizadi/BSF-Custom-Emotions-Robust-20260326-0611")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Moeinizadi/BSF-Custom-Emotions-Robust-20260326-0611") model = AutoModelForSequenceClassification.from_pretrained("Moeinizadi/BSF-Custom-Emotions-Robust-20260326-0611") - Notebooks
- Google Colab
- Kaggle
BSF-Custom-Emotions-Robust-20260326-0611
This model is a fine-tuned version of SamLowe/roberta-base-go_emotions on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4447
- Macro F1: 0.3254
- Micro F1: 0.4388
- Weighted F1: 0.5211
- Macro Precision: 0.2433
- Macro Recall: 0.7818
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: 1e-05
- train_batch_size: 16
- eval_batch_size: 32
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 28
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Macro F1 | Micro F1 | Weighted F1 | Macro Precision | Macro Recall |
|---|---|---|---|---|---|---|---|---|
| 0.8379 | 1.0 | 160 | 0.5140 | 0.2718 | 0.4097 | 0.4742 | 0.1869 | 0.6396 |
| 0.4754 | 2.0 | 320 | 0.4563 | 0.291 | 0.409 | 0.4959 | 0.1926 | 0.7943 |
| 0.4343 | 3.0 | 480 | 0.4447 | 0.3254 | 0.4388 | 0.5211 | 0.2433 | 0.7818 |
Framework versions
- Transformers 5.3.0
- Pytorch 2.5.1+cu121
- Datasets 4.8.4
- Tokenizers 0.22.2
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Model tree for Moeinizadi/BSF-Custom-Emotions-Robust-20260326-0611
Base model
SamLowe/roberta-base-go_emotions