Text Classification
Transformers
Safetensors
modernbert
classification
Generated from Trainer
text-embeddings-inference
Instructions to use carmengoar/clasificador-imdb-ej2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use carmengoar/clasificador-imdb-ej2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="carmengoar/clasificador-imdb-ej2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("carmengoar/clasificador-imdb-ej2") model = AutoModelForSequenceClassification.from_pretrained("carmengoar/clasificador-imdb-ej2") - Notebooks
- Google Colab
- Kaggle
clasificador-imdb-ej2
This model is a fine-tuned version of answerdotai/ModernBERT-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6255
- Accuracy: 0.905
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 50 | 0.4281 | 0.795 |
| No log | 2.0 | 100 | 0.3974 | 0.865 |
| No log | 3.0 | 150 | 0.3796 | 0.92 |
| No log | 4.0 | 200 | 0.6756 | 0.895 |
| No log | 5.0 | 250 | 0.6255 | 0.905 |
Framework versions
- Transformers 5.4.0
- Pytorch 2.10.0+cu128
- Datasets 4.8.4
- Tokenizers 0.22.2
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Model tree for carmengoar/clasificador-imdb-ej2
Base model
answerdotai/ModernBERT-base