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Tanor
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SRGPTSENTNEG0

Text Classification
Transformers
PyTorch
Serbian
gpt2
serbian
sentiment-analysis
wordnet
sentiwordnet
lexicon-induction
Model card Files
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update model card 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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  This model is a fine-tuned version of [Tanor/SRGPTSENTNEG0](https://huggingface.co/Tanor/SRGPTSENTNEG0) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1910
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- - F1: 0.2927
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  ## Model description
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@@ -43,22 +44,21 @@ The following hyperparameters were used during training:
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  - total_train_batch_size: 4
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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: 10
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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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- | 0.0885 | 1.0 | 2973 | 0.0990 | 0.0 |
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- | 0.0481 | 2.0 | 5947 | 0.0966 | 0.4138 |
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- | 0.0205 | 3.0 | 8921 | 0.1407 | 0.2857 |
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- | 0.0213 | 4.0 | 11895 | 0.1228 | 0.2273 |
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- | 0.002 | 5.0 | 14868 | 0.1910 | 0.2927 |
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  ### Framework versions
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- - Transformers 4.30.2
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- - Pytorch 2.0.1
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- - Datasets 2.13.1
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  - Tokenizers 0.13.3
 
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  ---
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+ base_model: Tanor/SRGPTSENTNEG0
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  tags:
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  - generated_from_trainer
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  metrics:
 
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  This model is a fine-tuned version of [Tanor/SRGPTSENTNEG0](https://huggingface.co/Tanor/SRGPTSENTNEG0) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.1405
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+ - F1: 0.4615
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  ## Model description
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  - total_train_batch_size: 4
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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: 32
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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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+ | 0.0849 | 1.0 | 2666 | 0.0868 | 0.0 |
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+ | 0.0581 | 2.0 | 5332 | 0.0976 | 0.3077 |
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+ | 0.0437 | 3.0 | 7998 | 0.1228 | 0.3529 |
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+ | 0.0119 | 4.0 | 10665 | 0.1405 | 0.4615 |
 
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  ### Framework versions
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+ - Transformers 4.31.0
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+ - Pytorch 2.1.0.dev20230801
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+ - Datasets 2.14.2
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  - Tokenizers 0.13.3