Text Classification
Transformers
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use phunganhsang/XMLRoberta_Dataset9kMetaGemini with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use phunganhsang/XMLRoberta_Dataset9kMetaGemini with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="phunganhsang/XMLRoberta_Dataset9kMetaGemini")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("phunganhsang/XMLRoberta_Dataset9kMetaGemini") model = AutoModelForSequenceClassification.from_pretrained("phunganhsang/XMLRoberta_Dataset9kMetaGemini") - Notebooks
- Google Colab
- Kaggle
XMLRoberta_Dataset9kMetaGemini
This model is a fine-tuned version of FacebookAI/xlm-roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3230
- Accuracy: 0.9385
- F1: 0.9385
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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| No log | 1.9608 | 200 | 0.1949 | 0.9365 | 0.9320 |
| 0.4342 | 3.9216 | 400 | 0.1815 | 0.9447 | 0.9461 |
| 0.1888 | 5.8824 | 600 | 0.2112 | 0.9365 | 0.9372 |
| 0.1157 | 7.8431 | 800 | 0.2231 | 0.9365 | 0.9372 |
| 0.0835 | 9.8039 | 1000 | 0.2487 | 0.9406 | 0.9407 |
| 0.0611 | 11.7647 | 1200 | 0.3141 | 0.9365 | 0.9352 |
| 0.0387 | 13.7255 | 1400 | 0.3055 | 0.9385 | 0.9378 |
| 0.0332 | 15.6863 | 1600 | 0.3221 | 0.9406 | 0.9408 |
| 0.0232 | 17.6471 | 1800 | 0.3318 | 0.9344 | 0.9345 |
| 0.0205 | 19.6078 | 2000 | 0.3230 | 0.9385 | 0.9385 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1
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Model tree for phunganhsang/XMLRoberta_Dataset9kMetaGemini
Base model
FacebookAI/xlm-roberta-base