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sentiment-model-saagie

Text Classification
Transformers
PyTorch
bert
Generated from Trainer
text-embeddings-inference
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update model card README.md

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@@ -15,13 +15,11 @@ model-index:
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  dataset:
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  name: sst2
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  type: sst2
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- config: default
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- split: validation
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  args: default
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.7883333333333333
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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
@@ -31,8 +29,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [prajjwal1/bert-tiny](https://huggingface.co/prajjwal1/bert-tiny) on the sst2 dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.5579
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- - Accuracy: 0.7883
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  ## Model description
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@@ -63,14 +61,14 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | 0.5178 | 1.0 | 1500 | 0.4748 | 0.7817 |
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- | 0.3797 | 2.0 | 3000 | 0.5265 | 0.7833 |
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- | 0.3345 | 3.0 | 4500 | 0.5579 | 0.7883 |
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  ### Framework versions
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- - Transformers 4.30.2
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- - Pytorch 2.0.1+cu117
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- - Datasets 2.13.1
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- - Tokenizers 0.13.3
 
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  dataset:
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  name: sst2
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  type: sst2
 
 
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  args: default
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.7916666666666666
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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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  This model is a fine-tuned version of [prajjwal1/bert-tiny](https://huggingface.co/prajjwal1/bert-tiny) on the sst2 dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.5457
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+ - Accuracy: 0.7917
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 0.5174 | 1.0 | 1500 | 0.4787 | 0.765 |
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+ | 0.379 | 2.0 | 3000 | 0.5247 | 0.7867 |
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+ | 0.3362 | 3.0 | 4500 | 0.5457 | 0.7917 |
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  ### Framework versions
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+ - Transformers 4.18.0
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+ - Pytorch 1.8.1
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+ - Datasets 2.12.0
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+ - Tokenizers 0.12.1