pabRomero
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BioMedRoBERTa-finetuned-ner-pablo-just-classifier

Token Classification

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pabRomero commited on Aug 22

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@@ -20,11 +20,11 @@ should probably proofread and complete it, then remove this comment. -->
 This model is a fine-tuned version of [allenai/biomed_roberta_base](https://huggingface.co/allenai/biomed_roberta_base) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.1220
-- Precision: 0.6776
-- Recall: 0.6935
-- F1: 0.6854
-- Accuracy: 0.9668
 ## Model description
@@ -44,8 +44,8 @@ More information needed
 The following hyperparameters were used during training:
 - learning_rate: 0.1
-- train_batch_size: 512
-- eval_batch_size: 512
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
@@ -55,13 +55,13 @@ The following hyperparameters were used during training:
 ### Training results
-| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
-|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| No log        | 1.0   | 23   | 0.2632          | 0.5303    | 0.6291 | 0.5755 | 0.9548   |
-| No log        | 2.0   | 46   | 0.1581          | 0.6207    | 0.6712 | 0.6450 | 0.9630   |
-| No log        | 3.0   | 69   | 0.1357          | 0.6494    | 0.6856 | 0.6670 | 0.9652   |
-| No log        | 4.0   | 92   | 0.1245          | 0.6658    | 0.6919 | 0.6786 | 0.9664   |
-| No log        | 5.0   | 115  | 0.1220          | 0.6776    | 0.6935 | 0.6854 | 0.9668   |
 ### Framework versions

 This model is a fine-tuned version of [allenai/biomed_roberta_base](https://huggingface.co/allenai/biomed_roberta_base) on the None dataset.
 It achieves the following results on the evaluation set:
+- Loss: 0.1276
+- Precision: 0.6818
+- Recall: 0.7031
+- F1: 0.6923
+- Accuracy: 0.9672
 ## Model description
 The following hyperparameters were used during training:
 - learning_rate: 0.1
+- train_batch_size: 2
+- eval_batch_size: 2
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 ### Training results
+| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.7191        | 1.0   | 2509  | 0.5248          | 0.5127    | 0.6334 | 0.5667 | 0.9486   |
+| 0.5382        | 2.0   | 5018  | 0.4280          | 0.5378    | 0.6500 | 0.5886 | 0.9556   |
+| 0.3968        | 3.0   | 7527  | 0.3095          | 0.4997    | 0.6714 | 0.5730 | 0.9531   |
+| 0.2528        | 4.0   | 10036 | 0.1872          | 0.5631    | 0.6850 | 0.6181 | 0.9599   |
+| 0.1541        | 5.0   | 12545 | 0.1276          | 0.6818    | 0.7031 | 0.6923 | 0.9672   |
 ### Framework versions