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README.md
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---
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license: mit
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base_model: 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-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-roberta-large
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This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.3381
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- Accuracy: 0.9053
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- F1: 0.9056
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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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| 0.3302 | 0.4997 | 1533 | 0.2972 | 0.8940 | 0.8934 |
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| 0.3139 | 0.9993 | 3066 | 0.2751 | 0.9027 | 0.9030 |
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| 0.242 | 1.4990 | 4599 | 0.2866 | 0.9030 | 0.9030 |
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| 0.2627 | 1.9987 | 6132 | 0.2921 | 0.9065 | 0.9066 |
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| 0.1818 | 2.4984 | 7665 | 0.3049 | 0.9035 | 0.9038 |
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| 0.1932 | 2.9980 | 9198 | 0.3153 | 0.9039 | 0.9038 |
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| 0.1457 | 3.4977 | 10731 | 0.3381 | 0.9053 | 0.9056 |
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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 1421499516
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version https://git-lfs.github.com/spec/v1
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size 1421499516
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