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update model card README.md
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README.md
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---
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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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- recall
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- precision
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model-index:
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- name: sentiment-roberta-e8-b16
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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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# sentiment-roberta-e8-b16
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This model is a fine-tuned version of [siebert/sentiment-roberta-large-english](https://huggingface.co/siebert/sentiment-roberta-large-english) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.7439
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- F1: 0.7547
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- Recall: 0.7547
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- Precision: 0.7547
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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: 2e-05
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- train_batch_size: 16
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- eval_batch_size: 16
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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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- num_epochs: 8
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | F1 | Recall | Precision |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:---------:|
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| No log | 1.0 | 375 | 0.7842 | 0.7224 | 0.7224 | 0.7224 |
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| 0.7132 | 2.0 | 750 | 0.7851 | 0.7547 | 0.7547 | 0.7547 |
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| 0.3587 | 3.0 | 1125 | 1.2599 | 0.7493 | 0.7493 | 0.7493 |
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| 0.2361 | 4.0 | 1500 | 1.2364 | 0.7628 | 0.7628 | 0.7628 |
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| 0.2361 | 5.0 | 1875 | 1.3809 | 0.7709 | 0.7709 | 0.7709 |
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| 0.138 | 6.0 | 2250 | 1.5058 | 0.7682 | 0.7682 | 0.7682 |
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| 0.1027 | 7.0 | 2625 | 1.6364 | 0.7574 | 0.7574 | 0.7574 |
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| 0.0493 | 8.0 | 3000 | 1.7439 | 0.7547 | 0.7547 | 0.7547 |
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### Framework versions
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- Transformers 4.30.2
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- Pytorch 2.0.1+cu118
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- Datasets 2.13.1
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- Tokenizers 0.13.3
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