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README.md
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license: apache-2.0
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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- f1
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model-index:
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- name: finetuning-sentiment-model-3000-samples
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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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# finetuning-sentiment-model-3000-samples
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on
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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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- num_epochs:
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### Training results
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- Transformers 4.23.1
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- Pytorch 1.12.1+cu113
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- Tokenizers 0.13.1
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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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- imdb
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metrics:
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- accuracy
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- f1
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model-index:
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- name: finetuning-sentiment-model-3000-samples
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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: imdb
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type: imdb
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config: plain_text
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split: train
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args: plain_text
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.8866666666666667
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- name: F1
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type: f1
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value: 0.8903225806451613
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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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# finetuning-sentiment-model-3000-samples
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the imdb dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.3498
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- Accuracy: 0.8867
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- F1: 0.8903
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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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- num_epochs: 4
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### Training results
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- Transformers 4.23.1
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- Pytorch 1.12.1+cu113
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- Datasets 2.5.2
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- Tokenizers 0.13.1
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