End of training

README.md

@@ -2,6 +2,11 @@
 base_model: allenai/scibert_scivocab_uncased
 tags:
 - generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
 model-index:
 - name: scibert-ner
   results: []
@@ -13,6 +18,12 @@ should probably proofread and complete it, then remove this comment. -->
 # scibert-ner
 
 This model is a fine-tuned version of [allenai/scibert_scivocab_uncased](https://huggingface.co/allenai/scibert_scivocab_uncased) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1809
+- Precision: 0.4499
+- Recall: 0.4637
+- F1: 0.4567
+- Accuracy: 0.9536
 
 ## Model description
 
@@ -37,13 +48,17 @@ The following hyperparameters were used during training:
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 1
+- num_epochs: 5
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| No log        | 1.0   | 60   | 0.2441          | 0.3858    | 0.1369 | 0.2021 | 0.9461   |
+| No log        | 1.0   | 60   | 0.1967          | 0.3563    | 0.3184 | 0.3363 | 0.9509   |
+| No log        | 2.0   | 120  | 0.1726          | 0.4077    | 0.3855 | 0.3963 | 0.9525   |
+| No log        | 3.0   | 180  | 0.1723          | 0.4204    | 0.4721 | 0.4447 | 0.9529   |
+| No log        | 4.0   | 240  | 0.1775          | 0.4248    | 0.4735 | 0.4478 | 0.9526   |
+| No log        | 5.0   | 300  | 0.1809          | 0.4499    | 0.4637 | 0.4567 | 0.9536   |
 
 
 ### Framework versions

pytorch_model.bin

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:7165150c7757e87b5362763889565cbf734ead88cc6f2ec7d434a610642cfe39
+oid sha256:fef43e720a294eb727cf9d3b1d3c45486bd093432d0259e7e18e3a1ff702b6e1
 size 437425830