metadata
library_name: transformers
license: mit
base_model: MoritzLaurer/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: Bert-Contact-NLI
results: []
datasets:
- kiddothe2b/contract-nli
pipeline_tag: zero-shot-classification
Bert-Contact-NLI
This model is a fine-tuned version of MoritzLaurer/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.9601
- Model Preparation Time: 0.0101
- Accuracy: 0.6358
- Precision: 0.6154
- Recall: 0.6254
- F1: 0.6161
- Ratio: 0.4969
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
- 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
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Accuracy | Precision | Recall | F1 | Ratio |
|---|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 95 | 0.9601 | 0.0101 | 0.6358 | 0.6154 | 0.6254 | 0.6161 | 0.4969 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3