End of training
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README.md
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tags:
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- generated_from_trainer
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metrics:
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- f1
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model-index:
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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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#
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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.
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## Model description
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- seed: 42
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: linear
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- num_epochs:
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | F1 |
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### Framework versions
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tags:
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- generated_from_trainer
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metrics:
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- precision
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- recall
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- f1
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model-index:
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- name: amazon_sentiment_clfn
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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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# amazon_sentiment_clfn
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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: 0.2018
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- Precision: 0.7804
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- Recall: 0.6077
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- F1: 0.6833
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## Model description
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- seed: 42
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: linear
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- num_epochs: 5
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 |
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|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|
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| 0.2019 | 1.0 | 9229 | 0.2018 | 0.7804 | 0.6077 | 0.6833 |
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| 0.1714 | 2.0 | 18458 | 0.2170 | 0.7279 | 0.7191 | 0.7234 |
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| 0.1337 | 3.0 | 27687 | 0.2890 | 0.7035 | 0.7220 | 0.7126 |
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| 0.0895 | 4.0 | 36916 | 0.3820 | 0.7291 | 0.6881 | 0.7080 |
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| 0.0693 | 5.0 | 46145 | 0.4428 | 0.7309 | 0.6824 | 0.7058 |
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### Framework versions
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model.safetensors
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