pabRomero
/

BioMedRoBERTa-finetuned-ner-pablo-just-classifier

@@ -21,11 +21,11 @@ should probably proofread and complete it, then remove this comment. -->
 This model is a fine-tuned version of [emilyalsentzer/Bio_ClinicalBERT](https://huggingface.co/emilyalsentzer/Bio_ClinicalBERT) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.1150
-- Precision: 0.6869
-- Recall: 0.7076
-- F1: 0.6971
-- Accuracy: 0.9677
 ## Model description
@@ -44,12 +44,12 @@ More information needed
 ### Training hyperparameters
 The following hyperparameters were used during training:
-- learning_rate: 0.1
-- train_batch_size: 128
-- eval_batch_size: 128
 - seed: 42
 - gradient_accumulation_steps: 4
-- total_train_batch_size: 512
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: cosine_with_restarts
 - lr_scheduler_warmup_ratio: 0.05
@@ -60,16 +60,16 @@ The following hyperparameters were used during training:
 | Training Loss | Epoch  | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| No log        | 0.9655 | 14   | 0.3729          | 0.4205    | 0.6119 | 0.4985 | 0.9430   |
-| No log        | 2.0    | 29   | 0.2544          | 0.5272    | 0.6683 | 0.5894 | 0.9574   |
-| No log        | 2.9655 | 43   | 0.2117          | 0.5702    | 0.6884 | 0.6238 | 0.9604   |
-| No log        | 4.0    | 58   | 0.1747          | 0.5934    | 0.7001 | 0.6424 | 0.9628   |
-| No log        | 4.9655 | 72   | 0.1420          | 0.6280    | 0.6827 | 0.6542 | 0.9642   |
-| No log        | 6.0    | 87   | 0.1287          | 0.6639    | 0.7033 | 0.6830 | 0.9667   |
-| No log        | 6.9655 | 101  | 0.1309          | 0.6471    | 0.7009 | 0.6729 | 0.9654   |
-| No log        | 8.0    | 116  | 0.1260          | 0.6349    | 0.7199 | 0.6748 | 0.9652   |
-| No log        | 8.9655 | 130  | 0.1159          | 0.6621    | 0.7118 | 0.6860 | 0.9670   |
-| No log        | 9.6552 | 140  | 0.1150          | 0.6869    | 0.7076 | 0.6971 | 0.9677   |
 ### Framework versions

 This model is a fine-tuned version of [emilyalsentzer/Bio_ClinicalBERT](https://huggingface.co/emilyalsentzer/Bio_ClinicalBERT) on the None dataset.
 It achieves the following results on the evaluation set:
+- Loss: 0.1228
+- Precision: 0.6701
+- Recall: 0.6809
+- F1: 0.6754
+- Accuracy: 0.9657
 ## Model description
 ### Training hyperparameters
 The following hyperparameters were used during training:
+- learning_rate: 0.01
+- train_batch_size: 512
+- eval_batch_size: 512
 - seed: 42
 - gradient_accumulation_steps: 4
+- total_train_batch_size: 2048
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: cosine_with_restarts
 - lr_scheduler_warmup_ratio: 0.05
 | Training Loss | Epoch  | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 0.9697 | 16   | 0.2938          | 0.4425    | 0.5130 | 0.4751 | 0.9361   |
+| No log        | 2.0    | 33   | 0.1815          | 0.5546    | 0.5873 | 0.5705 | 0.9535   |
+| No log        | 2.9697 | 49   | 0.1617          | 0.5838    | 0.6189 | 0.6008 | 0.9575   |
+| No log        | 4.0    | 66   | 0.1482          | 0.6070    | 0.6396 | 0.6229 | 0.9602   |
+| No log        | 4.9697 | 82   | 0.1340          | 0.6465    | 0.6563 | 0.6513 | 0.9633   |
+| No log        | 6.0    | 99   | 0.1306          | 0.6561    | 0.6638 | 0.6599 | 0.9641   |
+| No log        | 6.9697 | 115  | 0.1290          | 0.6569    | 0.6705 | 0.6636 | 0.9645   |
+| No log        | 8.0    | 132  | 0.1246          | 0.6664    | 0.6794 | 0.6728 | 0.9654   |
+| No log        | 8.9697 | 148  | 0.1230          | 0.6699    | 0.6793 | 0.6745 | 0.9656   |
+| No log        | 9.6970 | 160  | 0.1228          | 0.6701    | 0.6809 | 0.6754 | 0.9657   |
 ### Framework versions