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Browse files- README.md +70 -0
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README.md
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---
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license: mit
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base_model: xlm-roberta-large
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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- f1
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model-index:
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- name: fine-tuned-NLI-mnli_original-with-xlm-roberta-large
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# fine-tuned-NLI-mnli_original-with-xlm-roberta-large
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This model is a fine-tuned version of [xlm-roberta-large](https://huggingface.co/xlm-roberta-large) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.3833
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- Accuracy: 0.8879
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- F1: 0.8881
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 1e-05
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- train_batch_size: 8
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- eval_batch_size: 8
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- seed: 42
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- gradient_accumulation_steps: 16
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- total_train_batch_size: 128
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 10
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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|:-------------:|:------:|:-----:|:---------------:|:--------:|:------:|
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| 0.3931 | 0.4997 | 1533 | 0.3416 | 0.8697 | 0.8695 |
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| 0.3529 | 0.9993 | 3066 | 0.3214 | 0.8825 | 0.8829 |
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| 0.2985 | 1.4990 | 4599 | 0.3312 | 0.8872 | 0.8877 |
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| 0.299 | 1.9987 | 6132 | 0.3209 | 0.8881 | 0.8884 |
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| 0.2349 | 2.4984 | 7665 | 0.3322 | 0.8851 | 0.8856 |
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| 0.2433 | 2.9980 | 9198 | 0.3324 | 0.8866 | 0.8869 |
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| 0.1912 | 3.4977 | 10731 | 0.3833 | 0.8879 | 0.8881 |
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### Framework versions
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- Transformers 4.42.3
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- Pytorch 1.13.1+cu117
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- Datasets 2.2.0
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- Tokenizers 0.19.1
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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-
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size 2239622772
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version https://git-lfs.github.com/spec/v1
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size 2239622772
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