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sameearif
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bert-large-csb

Text Classification
Transformers
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Model card Files
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Training in progress, epoch 1

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Files changed (5) hide show
  1. README.md +21 -19
  2. model.safetensors +1 -1
  3. roberta-large_best/model.safetensors +1 -1
  4. roberta-large_best/training_args.bin +1 -1
  5. training_args.bin +1 -1
README.md CHANGED
@@ -1,27 +1,27 @@
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  ---
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  library_name: transformers
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- license: apache-2.0
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- base_model: google-bert/bert-large-uncased
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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: bert-large-csb
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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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  should probably proofread and complete it, then remove this comment. -->
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- # bert-large-csb
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- This model is a fine-tuned version of [google-bert/bert-large-uncased](https://huggingface.co/google-bert/bert-large-uncased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.5239
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- - Accuracy: 0.8637
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- - F1: 0.8638
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  ## Model description
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@@ -40,10 +40,12 @@ 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: 2e-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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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  - num_epochs: 10
@@ -52,16 +54,16 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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- | 0.4506 | 1.0 | 455 | 0.4215 | 0.7890 | 0.7831 |
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- | 0.2919 | 2.0 | 910 | 0.4337 | 0.8505 | 0.8505 |
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- | 0.3034 | 3.0 | 1365 | 0.5239 | 0.8637 | 0.8638 |
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- | 0.2416 | 4.0 | 1820 | 0.5891 | 0.8527 | 0.8527 |
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- | 0.0793 | 5.0 | 2275 | 0.8805 | 0.8374 | 0.8371 |
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- | 0.0385 | 6.0 | 2730 | 1.1213 | 0.8396 | 0.8384 |
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- | 0.0215 | 7.0 | 3185 | 1.1417 | 0.8440 | 0.8437 |
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- | 0.0001 | 8.0 | 3640 | 1.3328 | 0.8484 | 0.8482 |
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- | 0.0001 | 9.0 | 4095 | 1.3534 | 0.8418 | 0.8416 |
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- | 0.0165 | 10.0 | 4550 | 1.4137 | 0.8418 | 0.8415 |
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  ### Framework versions
 
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  ---
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  library_name: transformers
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+ license: mit
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+ base_model: FacebookAI/roberta-large
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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: roberta-large-csb
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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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  should probably proofread and complete it, then remove this comment. -->
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+ # roberta-large-csb
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+ This model is a fine-tuned version of [FacebookAI/roberta-large](https://huggingface.co/FacebookAI/roberta-large) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.2625
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+ - Accuracy: 0.8857
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+ - F1: 0.8860
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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: 1e-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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+ - gradient_accumulation_steps: 2
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+ - total_train_batch_size: 16
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  - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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  - num_epochs: 10
 
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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+ | 0.3718 | 1.0 | 228 | 0.2774 | 0.8747 | 0.8748 |
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+ | 0.3126 | 2.0 | 456 | 0.2625 | 0.8857 | 0.8860 |
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+ | 0.2053 | 3.0 | 684 | 0.3058 | 0.8791 | 0.8787 |
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+ | 0.1797 | 4.0 | 912 | 0.4676 | 0.8615 | 0.8601 |
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+ | 0.1087 | 5.0 | 1140 | 0.8824 | 0.8330 | 0.8288 |
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+ | 0.0827 | 6.0 | 1368 | 0.9341 | 0.8637 | 0.8616 |
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+ | 0.0336 | 7.0 | 1596 | 0.9355 | 0.8571 | 0.8552 |
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+ | 0.0077 | 8.0 | 1824 | 0.9166 | 0.8725 | 0.8720 |
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+ | 0.0011 | 9.0 | 2052 | 0.9783 | 0.8747 | 0.8740 |
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+ | 0.0001 | 10.0 | 2280 | 1.0445 | 0.8703 | 0.8692 |
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  ### Framework versions
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