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jay0911
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ade_biobert_output

Text Classification
Transformers
Safetensors
bert
Generated from Trainer
text-embeddings-inference
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jay0911 commited on
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  1. README.md +21 -18
  2. model.safetensors +1 -1
README.md CHANGED
@@ -1,6 +1,6 @@
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  ---
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  library_name: transformers
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- base_model: dmis-lab/biobert-base-cased-v1.2
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  tags:
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  - generated_from_trainer
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  metrics:
@@ -17,14 +17,14 @@ should probably proofread and complete it, then remove this comment. -->
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  # ade_biobert_output
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- This model is a fine-tuned version of [dmis-lab/biobert-base-cased-v1.2](https://huggingface.co/dmis-lab/biobert-base-cased-v1.2) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.4138
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- - Precision: 0.8945
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- - Recall: 0.8822
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- - F1: 0.8853
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- - Recall Positive: 0.8887
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- - Recall Negative: 0.8798
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  ## Model description
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@@ -44,10 +44,10 @@ More information needed
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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: 4
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- - eval_batch_size: 4
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  - seed: 42
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- - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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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  - lr_scheduler_warmup_steps: 500
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  - num_epochs: 10
@@ -56,17 +56,20 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Recall Positive | Recall Negative |
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  |:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:------:|:---------------:|:---------------:|
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- | 0.4983 | 0.1063 | 500 | 0.5789 | 0.8609 | 0.7602 | 0.7700 | 0.9858 | 0.6640 |
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- | 0.4389 | 0.2126 | 1000 | 0.6829 | 0.8700 | 0.8639 | 0.8547 | 0.6031 | 0.9751 |
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- | 0.5353 | 0.3189 | 1500 | 0.4000 | 0.8974 | 0.8903 | 0.8922 | 0.8862 | 0.8921 |
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- | 0.6367 | 0.4253 | 2000 | 0.6262 | 0.4915 | 0.7011 | 0.5779 | 0.0 | 1.0 |
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- | 0.623 | 0.5316 | 2500 | 0.6189 | 0.4915 | 0.7011 | 0.5779 | 0.0 | 1.0 |
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- | 0.6653 | 0.6379 | 3000 | 0.6122 | 0.4915 | 0.7011 | 0.5779 | 0.0 | 1.0 |
 
 
 
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  ### Framework versions
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  - Transformers 4.55.0
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- - Pytorch 2.8.0
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  - Datasets 4.0.0
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  - Tokenizers 0.21.4
 
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  ---
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  library_name: transformers
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+ base_model: jay0911/fine-tuned-aemodel
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  tags:
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  - generated_from_trainer
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  metrics:
 
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  # ade_biobert_output
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+ This model is a fine-tuned version of [jay0911/fine-tuned-aemodel](https://huggingface.co/jay0911/fine-tuned-aemodel) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.3619
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+ - Precision: 0.9353
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+ - Recall: 0.9358
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+ - F1: 0.9355
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+ - Recall Positive: 0.8686
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+ - Recall Negative: 0.9613
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  ## Model description
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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: Use OptimizerNames.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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  - lr_scheduler_warmup_steps: 500
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  - num_epochs: 10
 
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Recall Positive | Recall Negative |
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  |:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:------:|:---------------:|:---------------:|
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+ | 0.1921 | 0.2126 | 500 | 0.2565 | 0.9347 | 0.9332 | 0.9337 | 0.9147 | 0.9412 |
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+ | 0.1893 | 0.4252 | 1000 | 0.2461 | 0.9409 | 0.9392 | 0.9397 | 0.9289 | 0.9436 |
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+ | 0.2207 | 0.6378 | 1500 | 0.2583 | 0.9421 | 0.9418 | 0.9419 | 0.9104 | 0.9551 |
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+ | 0.1706 | 0.8503 | 2000 | 0.3926 | 0.9216 | 0.9205 | 0.9183 | 0.7866 | 0.9776 |
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+ | 0.1219 | 1.0629 | 2500 | 0.3413 | 0.9373 | 0.9354 | 0.9359 | 0.9246 | 0.9400 |
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+ | 0.1097 | 1.2755 | 3000 | 0.3073 | 0.9453 | 0.9456 | 0.9453 | 0.8919 | 0.9685 |
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+ | 0.1645 | 1.4881 | 3500 | 0.2700 | 0.9433 | 0.9430 | 0.9431 | 0.9118 | 0.9563 |
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+ | 0.2348 | 1.7007 | 4000 | 0.2449 | 0.9452 | 0.9456 | 0.9452 | 0.8876 | 0.9703 |
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+ | 0.2718 | 1.9133 | 4500 | 0.2304 | 0.9425 | 0.9426 | 0.9425 | 0.8990 | 0.9612 |
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  ### Framework versions
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  - Transformers 4.55.0
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+ - Pytorch 2.6.0+cu124
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  - Datasets 4.0.0
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  - Tokenizers 0.21.4
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