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---
license: mit
base_model: MoritzLaurer/mDeBERTa-v3-base-mnli-xnli
tags:
- generated_from_trainer
metrics:
- f1
- recall
- accuracy
- precision
model-index:
- name: mDeBERTa-v3-base-xnli-multilingual-nli-2mil7-base-fine-tuned-text-classificarion-ds-ss
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# mDeBERTa-v3-base-xnli-multilingual-nli-2mil7-base-fine-tuned-text-classificarion-ds-ss
This model is a fine-tuned version of [MoritzLaurer/mDeBERTa-v3-base-mnli-xnli](https://huggingface.co/MoritzLaurer/mDeBERTa-v3-base-mnli-xnli) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0473
- F1: 0.7427
- Recall: 0.7662
- Accuracy: 0.7662
- Precision: 0.7444
## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Recall | Accuracy | Precision |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:--------:|:---------:|
| 3.4822 | 1.0 | 883 | 2.0495 | 0.3963 | 0.4790 | 0.4790 | 0.3791 |
| 1.6347 | 2.0 | 1766 | 1.2672 | 0.6622 | 0.7030 | 0.7030 | 0.6535 |
| 1.0807 | 3.0 | 2649 | 1.0711 | 0.7172 | 0.7420 | 0.7420 | 0.7065 |
| 0.8958 | 4.0 | 3532 | 1.0654 | 0.7232 | 0.7489 | 0.7489 | 0.7218 |
| 0.7766 | 5.0 | 4415 | 1.0473 | 0.7427 | 0.7662 | 0.7662 | 0.7444 |
### Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
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