update model card README.md
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README.md
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---
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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:
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- tweet_eval
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metrics:
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- f1
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model-index:
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- name: hate_trained_final
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results:
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- task:
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name: Text Classification
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type: text-classification
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dataset:
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name: tweet_eval
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type: tweet_eval
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args: hate
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metrics:
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- name: F1
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type: f1
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value: 0.7697890540753396
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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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# hate_trained_final
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the tweet_eval dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.5543
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- F1: 0.7698
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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: 5.460503761236833e-06
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- train_batch_size: 8
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- eval_batch_size: 8
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- seed: 0
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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: 4
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | F1 |
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|:-------------:|:-----:|:----:|:---------------:|:------:|
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| 0.463 | 1.0 | 1125 | 0.5213 | 0.7384 |
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| 0.3943 | 2.0 | 2250 | 0.5134 | 0.7534 |
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| 0.3407 | 3.0 | 3375 | 0.5400 | 0.7666 |
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| 0.3121 | 4.0 | 4500 | 0.5543 | 0.7698 |
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### Framework versions
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- Transformers 4.12.5
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- Pytorch 1.9.1
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- Datasets 1.16.1
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- Tokenizers 0.10.3
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