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pretoxtm-sentence-classifier

Text Classification
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Safetensors
English
bert
Generated from Trainer
text-embeddings-inference
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javicorvi/pretoxtm-sentence-classifier

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  1. README.md +12 -14
  2. config.json +1 -1
  3. model.safetensors +1 -1
  4. training_args.bin +2 -2
README.md CHANGED
@@ -20,11 +20,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext](https://huggingface.co/microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0802
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- - Precision: 0.9778
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- - Recall: 0.9801
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  - Accuracy: 0.9795
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- - F1: 0.9789
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  ## Model description
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@@ -43,28 +43,26 @@ 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: 7.755382954990098e-06
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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: 10
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | Accuracy | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:--------:|:------:|
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- | No log | 1.0 | 257 | 0.1410 | 0.9593 | 0.9684 | 0.9636 | 0.9628 |
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- | 0.1997 | 2.0 | 514 | 0.0802 | 0.9778 | 0.9801 | 0.9795 | 0.9789 |
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- | 0.1997 | 3.0 | 771 | 0.1103 | 0.9824 | 0.9848 | 0.9841 | 0.9836 |
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- | 0.0514 | 4.0 | 1028 | 0.1139 | 0.9798 | 0.9829 | 0.9818 | 0.9813 |
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- | 0.0514 | 5.0 | 1285 | 0.1208 | 0.9804 | 0.9821 | 0.9818 | 0.9812 |
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  ### Framework versions
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- - Transformers 4.39.2
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  - Pytorch 2.2.1+cu121
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  - Datasets 2.18.0
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  - Tokenizers 0.15.2
 
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  This model is a fine-tuned version of [microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext](https://huggingface.co/microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.1181
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+ - Precision: 0.9788
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+ - Recall: 0.9800
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  - Accuracy: 0.9795
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+ - F1: 0.9794
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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: 1.1848183151867784e-05
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+ - train_batch_size: 4
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  - eval_batch_size: 8
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+ - seed: 1
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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: 3
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | Accuracy | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:--------:|:------:|
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+ | 0.2543 | 1.0 | 514 | 0.1181 | 0.9788 | 0.9800 | 0.9795 | 0.9794 |
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+ | 0.1344 | 2.0 | 1028 | 0.1488 | 0.9767 | 0.9775 | 0.9773 | 0.9771 |
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+ | 0.0419 | 3.0 | 1542 | 0.1520 | 0.9767 | 0.9775 | 0.9773 | 0.9771 |
 
 
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  ### Framework versions
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+ - Transformers 4.39.3
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  - Pytorch 2.2.1+cu121
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  - Datasets 2.18.0
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  - Tokenizers 0.15.2
config.json CHANGED
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  "position_embedding_type": "absolute",
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  "problem_type": "single_label_classification",
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  "torch_dtype": "float32",
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- "transformers_version": "4.39.2",
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  "type_vocab_size": 2,
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  "use_cache": true,
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  "vocab_size": 30522
 
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  "position_embedding_type": "absolute",
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  "problem_type": "single_label_classification",
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  "torch_dtype": "float32",
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+ "transformers_version": "4.39.3",
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  "type_vocab_size": 2,
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  "use_cache": true,
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  "vocab_size": 30522
model.safetensors CHANGED
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