Julien Simon
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update model card README.md
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README.md
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license: apache-2.0
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tags:
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- generated_from_trainer
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datasets: juliensimon/amazon-shoe-reviews
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metrics:
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- accuracy
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- f1
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results: []
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---
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Accuracy: 0.
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- F1: [0.
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- Precision: [0.
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- Recall: [0.
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## Model description
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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: 1
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------------------------------------------------------:|:--------------------------------------------------------:|:--------------------------------------------------------:|
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### Framework versions
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- Transformers 4.
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- Pytorch
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- Datasets 2.
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- Tokenizers 0.
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license: apache-2.0
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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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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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# distilbert-amazon-shoe-reviews
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.9546
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- Accuracy: 0.5788
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- F1: [0.62939855 0.4656164 0.50839092 0.5594581 0.73356926]
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- Precision: [0.62705122 0.47043962 0.49258728 0.58103179 0.7255 ]
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- Recall: [0.63176353 0.46089109 0.52524222 0.53942912 0.74182004]
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## Model description
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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: 1
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------------------------------------------------------:|:--------------------------------------------------------:|:--------------------------------------------------------:|
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| 0.9611 | 1.0 | 2813 | 0.9546 | 0.5788 | [0.62939855 0.4656164 0.50839092 0.5594581 0.73356926] | [0.62705122 0.47043962 0.49258728 0.58103179 0.7255 ] | [0.63176353 0.46089109 0.52524222 0.53942912 0.74182004] |
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### Framework versions
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- Transformers 4.28.1
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- Pytorch 2.0.0+cu117
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- Datasets 2.12.0
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- Tokenizers 0.13.3
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