End of training

README.md

@@ -1,13 +1,40 @@
 ---
-license: mit
-base_model: xlm-roberta-large
+license: apache-2.0
+base_model: distilbert-base-cased
 tags:
 - generated_from_trainer
 datasets:
 - shipping_label_ner
+metrics:
+- precision
+- recall
+- f1
+- accuracy
 model-index:
 - name: ner_bert_model
-  results: []
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: shipping_label_ner
+      type: shipping_label_ner
+      config: shipping_label_ner
+      split: validation
+      args: shipping_label_ner
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.5178571428571429
+    - name: Recall
+      type: recall
+      value: 0.7837837837837838
+    - name: F1
+      type: f1
+      value: 0.6236559139784947
+    - name: Accuracy
+      type: accuracy
+      value: 0.7627118644067796
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -15,18 +42,13 @@ should probably proofread and complete it, then remove this comment. -->
 
 # ner_bert_model
 
-This model is a fine-tuned version of [xlm-roberta-large](https://huggingface.co/xlm-roberta-large) on the shipping_label_ner dataset.
+This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on the shipping_label_ner dataset.
 It achieves the following results on the evaluation set:
-- eval_loss: 0.1076
-- eval_precision: 0.9091
-- eval_recall: 0.9524
-- eval_f1: 0.9302
-- eval_accuracy: 0.9691
-- eval_runtime: 0.325
-- eval_samples_per_second: 15.384
-- eval_steps_per_second: 9.23
-- epoch: 13.0
-- step: 130
+- Loss: 1.2010
+- Precision: 0.5179
+- Recall: 0.7838
+- F1: 0.6237
+- Accuracy: 0.7627
 
 ## Model description
 
@@ -51,7 +73,33 @@ 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: 100
+- num_epochs: 20
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 14   | 0.6828          | 0.5179    | 0.7838 | 0.6237 | 0.7627   |
+| No log        | 2.0   | 28   | 0.8587          | 0.5273    | 0.7838 | 0.6304 | 0.7712   |
+| No log        | 3.0   | 42   | 0.7206          | 0.5577    | 0.7838 | 0.6517 | 0.8136   |
+| No log        | 4.0   | 56   | 0.8983          | 0.5370    | 0.7838 | 0.6374 | 0.7797   |
+| No log        | 5.0   | 70   | 0.6964          | 0.5472    | 0.7838 | 0.6444 | 0.8051   |
+| No log        | 6.0   | 84   | 0.9793          | 0.5179    | 0.7838 | 0.6237 | 0.7627   |
+| No log        | 7.0   | 98   | 0.6047          | 0.5472    | 0.7838 | 0.6444 | 0.8051   |
+| No log        | 8.0   | 112  | 1.0809          | 0.5179    | 0.7838 | 0.6237 | 0.7797   |
+| No log        | 9.0   | 126  | 1.1726          | 0.5179    | 0.7838 | 0.6237 | 0.7627   |
+| No log        | 10.0  | 140  | 1.0067          | 0.5179    | 0.7838 | 0.6237 | 0.7627   |
+| No log        | 11.0  | 154  | 1.1439          | 0.5088    | 0.7838 | 0.6170 | 0.7627   |
+| No log        | 12.0  | 168  | 0.8971          | 0.5370    | 0.7838 | 0.6374 | 0.7881   |
+| No log        | 13.0  | 182  | 1.0603          | 0.5179    | 0.7838 | 0.6237 | 0.7542   |
+| No log        | 14.0  | 196  | 1.2095          | 0.5179    | 0.7838 | 0.6237 | 0.7627   |
+| No log        | 15.0  | 210  | 1.2395          | 0.5179    | 0.7838 | 0.6237 | 0.7627   |
+| No log        | 16.0  | 224  | 1.2509          | 0.5179    | 0.7838 | 0.6237 | 0.7627   |
+| No log        | 17.0  | 238  | 1.2317          | 0.5179    | 0.7838 | 0.6237 | 0.7542   |
+| No log        | 18.0  | 252  | 1.2656          | 0.5179    | 0.7838 | 0.6237 | 0.7542   |
+| No log        | 19.0  | 266  | 1.1950          | 0.5179    | 0.7838 | 0.6237 | 0.7627   |
+| No log        | 20.0  | 280  | 1.2010          | 0.5179    | 0.7838 | 0.6237 | 0.7627   |
+
 
 ### Framework versions
 

model.safetensors

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 version https://git-lfs.github.com/spec/v1
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+oid sha256:31ebd2722d2253205c27e93a73ab8a0d704091579f1accc3e2e2bc8e5b666122
 size 260815972

runs/Mar27_05-22-59_4912d2a8deb3/events.out.tfevents.1711517435.4912d2a8deb3.761.1

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:670dc367d85d1df41cbbef99f752bbd87b6ee55495c9d38d437891f4ce166ac7
-size 13974
+oid sha256:7003774fb2c4b1d4d33dc2275ca0ec0f8546e30976488754722f4ba415e53ab7
+size 14800