Text Classification
Transformers
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use naive-puzzle/prox-doc-xlm-roberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use naive-puzzle/prox-doc-xlm-roberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="naive-puzzle/prox-doc-xlm-roberta-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("naive-puzzle/prox-doc-xlm-roberta-base") model = AutoModelForSequenceClassification.from_pretrained("naive-puzzle/prox-doc-xlm-roberta-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
prox-doc-xlm-roberta-base
This model is a fine-tuned version of FacebookAI/xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3884
- Accuracy: 0.8212
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: 64
- eval_batch_size: 128
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 0 | 0 | 0.6939 | 0.4947 |
| 0.4562 | 0.1002 | 251 | 0.4377 | 0.7956 |
| 0.369 | 0.2003 | 502 | 0.4421 | 0.8068 |
| 0.4306 | 0.3005 | 753 | 0.4042 | 0.8123 |
| 0.384 | 0.4006 | 1004 | 0.4016 | 0.8180 |
| 0.4115 | 0.5008 | 1255 | 0.3996 | 0.8177 |
| 0.4205 | 0.6010 | 1506 | 0.4070 | 0.8079 |
| 0.39 | 0.7011 | 1757 | 0.3883 | 0.8227 |
| 0.3902 | 0.8013 | 2008 | 0.3951 | 0.8179 |
| 0.369 | 0.9014 | 2259 | 0.3884 | 0.8212 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.4.1+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1
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Model tree for naive-puzzle/prox-doc-xlm-roberta-base
Base model
FacebookAI/xlm-roberta-base