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jorgeduardo13
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platzi-distilbert-model-similaritytexts-JorgeEnciso

Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
Eval Results
Inference Endpoints
Model card Files Community
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  1. README.md +11 -10
  2. pytorch_model.bin +1 -1
README.md CHANGED
@@ -23,10 +23,10 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.6838235294117647
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  - name: F1
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  type: f1
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- value: 0.8122270742358079
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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
@@ -36,9 +36,9 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the glue dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.6247
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- - Accuracy: 0.6838
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- - F1: 0.8122
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  ## Model description
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@@ -57,21 +57,22 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 0.0003
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  - train_batch_size: 8
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  - eval_batch_size: 8
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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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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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- | 0.6461 | 1.09 | 500 | 0.6242 | 0.6838 | 0.8122 |
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- | 0.6329 | 2.18 | 1000 | 0.6252 | 0.6838 | 0.8122 |
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- | 0.636 | 3.27 | 1500 | 0.6247 | 0.6838 | 0.8122 |
 
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  ### Framework versions
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.6887254901960784
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  - name: F1
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  type: f1
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+ value: 0.777583187390543
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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 [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the glue dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.6390
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+ - Accuracy: 0.6887
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+ - F1: 0.7776
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 5e-05
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  - train_batch_size: 8
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  - eval_batch_size: 8
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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: 5
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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+ | 0.6336 | 1.09 | 500 | 0.6239 | 0.6838 | 0.8122 |
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+ | 0.6337 | 2.18 | 1000 | 0.6223 | 0.6912 | 0.8158 |
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+ | 0.6076 | 3.27 | 1500 | 0.5871 | 0.7083 | 0.8126 |
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+ | 0.5585 | 4.36 | 2000 | 0.6390 | 0.6887 | 0.7776 |
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  ### Framework versions
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