santiviquez
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End of training
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README.md
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.
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- name: F1
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type: f1
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value: 0.
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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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This model is a fine-tuned version of [nlptown/bert-base-multilingual-uncased-sentiment](https://huggingface.co/nlptown/bert-base-multilingual-uncased-sentiment) on the amazon_reviews_multi dataset.
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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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## Model description
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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| No log | 1.0 | 94 | 0.
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| No log | 2.0 | 188 | 0.
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### Framework versions
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.7496463932107497
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- name: F1
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type: f1
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value: 0.7048383130660278
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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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This model is a fine-tuned version of [nlptown/bert-base-multilingual-uncased-sentiment](https://huggingface.co/nlptown/bert-base-multilingual-uncased-sentiment) on the amazon_reviews_multi dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.5919
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- Accuracy: 0.7496
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- F1: 0.7048
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## Model description
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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| No log | 1.0 | 94 | 0.5705 | 0.7539 | 0.6967 |
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| No log | 2.0 | 188 | 0.5919 | 0.7496 | 0.7048 |
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### Framework versions
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