santiviquez
commited on
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End of training
Browse files- README.md +9 -9
- pytorch_model.bin +1 -1
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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The following hyperparameters were used during training:
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- learning_rate: 2e-05
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- train_batch_size:
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- eval_batch_size:
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- seed: 42
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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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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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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: 0.7391304347826086
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- name: F1
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type: f1
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value: 0.7298701298701299
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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: 0.5437
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- Accuracy: 0.7391
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- F1: 0.7299
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## Model description
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The following hyperparameters were used during training:
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- learning_rate: 2e-05
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- train_batch_size: 32
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- eval_batch_size: 32
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- seed: 42
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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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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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| No log | 1.0 | 118 | 0.5791 | 0.8261 | 0.7944 |
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| No log | 2.0 | 236 | 0.5437 | 0.7391 | 0.7299 |
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### Framework versions
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pytorch_model.bin
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