Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use bif02/operons_function_conservation_511145 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bif02/operons_function_conservation_511145 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="bif02/operons_function_conservation_511145")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("bif02/operons_function_conservation_511145") model = AutoModelForSequenceClassification.from_pretrained("bif02/operons_function_conservation_511145", device_map="auto") - Notebooks
- Google Colab
- Kaggle
operons_function_conservation_511145
This model is a fine-tuned version of roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4048
- Accuracy: 0.8357
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: 3e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 0
- 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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 161 | 0.4003 | 0.8339 |
| No log | 2.0 | 322 | 0.3897 | 0.8147 |
| No log | 3.0 | 483 | 0.3740 | 0.8339 |
| 0.4213 | 4.0 | 644 | 0.3738 | 0.8234 |
| 0.4213 | 5.0 | 805 | 0.4300 | 0.8287 |
| 0.4213 | 6.0 | 966 | 0.4043 | 0.8357 |
| 0.3440 | 7.0 | 1127 | 0.4588 | 0.8234 |
| 0.3440 | 8.0 | 1288 | 0.4590 | 0.8129 |
| 0.3440 | 9.0 | 1449 | 0.5462 | 0.8059 |
| 0.2846 | 10.0 | 1610 | 0.5235 | 0.8042 |
Framework versions
- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2
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Model tree for bif02/operons_function_conservation_511145
Base model
FacebookAI/roberta-base