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bert-question-classifier

Text Classification
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bert
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text-embeddings-inference
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ai-research-lab/bert-question-classifier

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Files changed (4) hide show
  1. README.md +28 -23
  2. config.json +18 -0
  3. model.safetensors +1 -1
  4. tokenizer.json +10 -1
README.md CHANGED
@@ -21,11 +21,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.4053
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- - Accuracy: 0.9730
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- - Recall: 0.8657
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- - Precision: 0.8414
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- - F1: 0.8534
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  ## Model description
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@@ -44,7 +44,7 @@ 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: 9e-05
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  - train_batch_size: 4
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  - eval_batch_size: 4
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  - seed: 42
@@ -57,23 +57,28 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Recall | Precision | F1 |
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  |:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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- | No log | 0.0959 | 100 | 4.9052 | 0.8992 | 0.4299 | 0.4437 | 0.4367 |
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- | No log | 0.1918 | 200 | 3.9607 | 0.9324 | 0.6086 | 0.6331 | 0.6206 |
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- | No log | 0.2876 | 300 | 3.1200 | 0.9433 | 0.6929 | 0.6868 | 0.6898 |
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- | No log | 0.3835 | 400 | 2.8097 | 0.9529 | 0.7516 | 0.7363 | 0.7438 |
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- | 3.8292 | 0.4794 | 500 | 2.4593 | 0.9570 | 0.7677 | 0.7611 | 0.7644 |
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- | 3.8292 | 0.5753 | 600 | 2.1407 | 0.9621 | 0.8024 | 0.7851 | 0.7937 |
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- | 3.8292 | 0.6711 | 700 | 2.0963 | 0.9611 | 0.7882 | 0.7847 | 0.7864 |
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- | 3.8292 | 0.7670 | 800 | 1.8911 | 0.9638 | 0.8055 | 0.7983 | 0.8019 |
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- | 3.8292 | 0.8629 | 900 | 1.8706 | 0.9627 | 0.8018 | 0.7908 | 0.7962 |
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- | 2.0673 | 0.9588 | 1000 | 1.7311 | 0.9649 | 0.8282 | 0.7946 | 0.8111 |
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- | 2.0673 | 1.0547 | 1100 | 1.7874 | 0.9670 | 0.8235 | 0.8157 | 0.8196 |
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- | 2.0673 | 1.1505 | 1200 | 1.6227 | 0.9690 | 0.8362 | 0.8247 | 0.8304 |
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- | 2.0673 | 1.2464 | 1300 | 1.4544 | 0.9720 | 0.8496 | 0.8433 | 0.8464 |
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- | 2.0673 | 1.3423 | 1400 | 1.5178 | 0.9711 | 0.8533 | 0.8326 | 0.8428 |
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- | 1.4953 | 1.4382 | 1500 | 1.4053 | 0.9730 | 0.8657 | 0.8414 | 0.8534 |
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- | 1.4953 | 1.5340 | 1600 | 1.4916 | 0.9721 | 0.8626 | 0.8359 | 0.8490 |
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- | 1.4953 | 1.6299 | 1700 | 1.4541 | 0.9719 | 0.8601 | 0.8360 | 0.8479 |
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.9776
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+ - Accuracy: 0.9688
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+ - Recall: 0.8356
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+ - Precision: 0.8233
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+ - F1: 0.8294
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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: 4
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  - eval_batch_size: 4
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  - seed: 42
 
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Recall | Precision | F1 |
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  |:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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+ | No log | 0.0959 | 100 | 5.2538 | 0.8954 | 0.4113 | 0.4226 | 0.4169 |
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+ | No log | 0.1918 | 200 | 4.8785 | 0.9119 | 0.4529 | 0.5177 | 0.4831 |
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+ | No log | 0.2876 | 300 | 4.5415 | 0.9206 | 0.5307 | 0.5675 | 0.5485 |
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+ | No log | 0.3835 | 400 | 4.2158 | 0.9319 | 0.6238 | 0.6261 | 0.6249 |
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+ | 4.7973 | 0.4794 | 500 | 3.9246 | 0.9365 | 0.6445 | 0.6528 | 0.6487 |
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+ | 4.7973 | 0.5753 | 600 | 3.7378 | 0.9393 | 0.6749 | 0.6630 | 0.6689 |
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+ | 4.7973 | 0.6711 | 700 | 3.5841 | 0.9420 | 0.6849 | 0.6794 | 0.6821 |
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+ | 4.7973 | 0.7670 | 800 | 3.3128 | 0.9471 | 0.7255 | 0.7024 | 0.7138 |
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+ | 4.7973 | 0.8629 | 900 | 3.1501 | 0.9476 | 0.7261 | 0.7058 | 0.7158 |
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+ | 3.4614 | 0.9588 | 1000 | 2.9866 | 0.9498 | 0.7354 | 0.7189 | 0.7271 |
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+ | 3.4614 | 1.0547 | 1100 | 2.8197 | 0.9532 | 0.7509 | 0.7386 | 0.7447 |
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+ | 3.4614 | 1.1505 | 1200 | 2.6852 | 0.9544 | 0.7559 | 0.7457 | 0.7508 |
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+ | 3.4614 | 1.2464 | 1300 | 2.5284 | 0.9585 | 0.7776 | 0.7685 | 0.7730 |
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+ | 3.4614 | 1.3423 | 1400 | 2.4018 | 0.9612 | 0.7981 | 0.7802 | 0.7890 |
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+ | 2.6456 | 1.4382 | 1500 | 2.3255 | 0.9620 | 0.7996 | 0.7860 | 0.7927 |
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+ | 2.6456 | 1.5340 | 1600 | 2.2501 | 0.9630 | 0.8089 | 0.7891 | 0.7989 |
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+ | 2.6456 | 1.6299 | 1700 | 2.1575 | 0.9655 | 0.8229 | 0.8022 | 0.8124 |
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+ | 2.6456 | 1.7258 | 1800 | 2.0949 | 0.9658 | 0.8158 | 0.8095 | 0.8126 |
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+ | 2.6456 | 1.8217 | 1900 | 2.0348 | 0.9666 | 0.8282 | 0.8086 | 0.8183 |
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+ | 2.1476 | 1.9175 | 2000 | 1.9776 | 0.9688 | 0.8356 | 0.8233 | 0.8294 |
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+ | 2.1476 | 2.0134 | 2100 | 1.9170 | 0.9685 | 0.8390 | 0.8187 | 0.8287 |
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+ | 2.1476 | 2.1093 | 2200 | 1.8676 | 0.9685 | 0.8347 | 0.8214 | 0.828 |
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  ### Framework versions
config.json CHANGED
@@ -5,6 +5,24 @@
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  ],
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  "attention_probs_dropout_prob": 0.1,
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  "classifier_dropout": null,
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  "gradient_checkpointing": false,
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  "hidden_act": "gelu",
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  "hidden_dropout_prob": 0.1,
 
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  ],
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  "attention_probs_dropout_prob": 0.1,
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  "classifier_dropout": null,
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+ "custom_pipelines": {
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+ "question-classifier": {
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+ "default": {
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+ "model": {
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+ "pt": [
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+ "ai-research-lab/bert-question-classifier",
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+ "main"
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+ ]
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+ }
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+ },
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+ "impl": "classifier_pipeline.MultiTaskClassifierPipeline",
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+ "pt": [
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+ "AutoModelForSequenceClassification"
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+ ],
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+ "tf": [],
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+ "type": "text"
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+ }
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+ },
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  "gradient_checkpointing": false,
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  "hidden_act": "gelu",
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  "hidden_dropout_prob": 0.1,
model.safetensors CHANGED
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tokenizer.json CHANGED
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- "padding": null,
 
 
 
 
 
 
 
 
 
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+ "padding": {
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+ "direction": "Right",
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+ "pad_to_multiple_of": null,
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