Training complete

README.md

@@ -5,24 +5,9 @@ tags:
 - generated_from_trainer
 datasets:
 - clinc_oos
-metrics:
-- accuracy
 model-index:
 - name: distilbert-base-uncased-distilled-clinc
-  results:
-  - task:
-      name: Text Classification
-      type: text-classification
-    dataset:
-      name: clinc_oos
-      type: clinc_oos
-      config: plus
-      split: validation
-      args: plus
-    metrics:
-    - name: Accuracy
-      type: accuracy
-      value: 0.94
+  results: []
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -31,9 +16,6 @@ should probably proofread and complete it, then remove this comment. -->
 # distilbert-base-uncased-distilled-clinc
 
 This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the clinc_oos dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.1261
-- Accuracy: 0.94
 
 ## Model description
 
@@ -60,22 +42,6 @@ The following hyperparameters were used during training:
 - lr_scheduler_type: linear
 - num_epochs: 10
 
-### Training results
-
-| Training Loss | Epoch | Step | Validation Loss | Accuracy |
-|:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 1.2318        | 1.0   | 318  | 0.7448          | 0.7023   |
-| 0.5696        | 2.0   | 636  | 0.3308          | 0.8632   |
-| 0.2888        | 3.0   | 954  | 0.1941          | 0.9187   |
-| 0.1913        | 4.0   | 1272 | 0.1557          | 0.9284   |
-| 0.1563        | 5.0   | 1590 | 0.1417          | 0.9365   |
-| 0.1405        | 6.0   | 1908 | 0.1353          | 0.9387   |
-| 0.1318        | 7.0   | 2226 | 0.1316          | 0.9403   |
-| 0.1268        | 8.0   | 2544 | 0.1284          | 0.9426   |
-| 0.1239        | 9.0   | 2862 | 0.1266          | 0.9394   |
-| 0.122         | 10.0  | 3180 | 0.1261          | 0.94     |
-
-
 ### Framework versions
 
 - Transformers 4.34.1

config.json

@@ -320,7 +320,6 @@
   "n_heads": 12,
   "n_layers": 6,
   "pad_token_id": 0,
-  "problem_type": "single_label_classification",
   "qa_dropout": 0.1,
   "seq_classif_dropout": 0.2,
   "sinusoidal_pos_embds": false,

pytorch_model.bin

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training_args.bin

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