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distilroberta-base-wandb-week-3-complaints-classifier-1024

Text Classification
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PyTorch
roberta
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Eval Results
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update model card README.md

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@@ -22,16 +22,16 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.7935375363131338
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  - name: F1
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  type: f1
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- value: 0.7782286513484494
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  - name: Recall
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  type: recall
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- value: 0.7935375363131338
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  - name: Precision
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  type: precision
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- value: 0.7838508007361574
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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
@@ -41,11 +41,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on the consumer-finance-complaints dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.6228
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- - Accuracy: 0.7935
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- - F1: 0.7782
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- - Recall: 0.7935
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- - Precision: 0.7839
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  ## Model description
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@@ -64,7 +64,7 @@ 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: 0.00019154628432502008
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  - train_batch_size: 32
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  - eval_batch_size: 32
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  - seed: 42
@@ -78,9 +78,9 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Recall | Precision |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|
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- | 0.8624 | 0.61 | 1500 | 0.8468 | 0.7521 | 0.7215 | 0.7521 | 0.7083 |
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- | 0.743 | 1.22 | 3000 | 0.7668 | 0.7651 | 0.7417 | 0.7651 | 0.7383 |
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- | 0.6135 | 1.83 | 4500 | 0.6228 | 0.7935 | 0.7782 | 0.7935 | 0.7839 |
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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: 0.8279904184292339
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  - name: F1
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  type: f1
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+ value: 0.8236604095677945
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  - name: Recall
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  type: recall
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+ value: 0.8279904184292339
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  - name: Precision
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  type: precision
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+ value: 0.8235526237070518
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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 [distilroberta-base](https://huggingface.co/distilroberta-base) on the consumer-finance-complaints dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.5351
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+ - Accuracy: 0.8280
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+ - F1: 0.8237
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+ - Recall: 0.8280
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+ - Precision: 0.8236
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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: 9.027176214786854e-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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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Recall | Precision |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|
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+ | 0.7756 | 0.61 | 1500 | 0.7411 | 0.7647 | 0.7375 | 0.7647 | 0.7606 |
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+ | 0.5804 | 1.22 | 3000 | 0.6140 | 0.8088 | 0.8052 | 0.8088 | 0.8077 |
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+ | 0.5008 | 1.83 | 4500 | 0.5351 | 0.8280 | 0.8237 | 0.8280 | 0.8236 |
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  ### Framework versions