Training in progress, step 500

README.md

@@ -8,21 +8,21 @@ metrics:
 - recall
 - f1
 model-index:
-- name: BERT-ukpolitics
+- name: BERT-worldpolitics
   results: []
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 should probably proofread and complete it, then remove this comment. -->
 
-# BERT-ukpolitics
+# BERT-worldpolitics
 
 This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.1724
-- Precision: 0.5375
-- Recall: 0.4443
-- F1: 0.4865
+- Loss: 0.1773
+- Precision: 0.5895
+- Recall: 0.4879
+- F1: 0.5339
 
 ## Model description
 
@@ -53,14 +53,14 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|
-| No log        | 1.0   | 306  | 0.0898          | 0.5426    | 0.5597 | 0.5510 |
-| 0.1069        | 2.0   | 612  | 0.1054          | 0.6672    | 0.5720 | 0.6160 |
-| 0.1069        | 3.0   | 918  | 0.1102          | 0.6711    | 0.6241 | 0.6468 |
+| No log        | 1.0   | 306  | 0.1229          | 0.4522    | 0.3858 | 0.4164 |
+| 0.0968        | 2.0   | 612  | 0.1420          | 0.5316    | 0.5212 | 0.5264 |
+| 0.0968        | 3.0   | 918  | 0.1773          | 0.5895    | 0.4879 | 0.5339 |
 
 
 ### Framework versions
 
-- Transformers 4.40.1
+- Transformers 4.40.2
 - Pytorch 2.2.1+cu121
-- Datasets 2.19.0
+- Datasets 2.19.1
 - Tokenizers 0.19.1

config.json

@@ -29,7 +29,7 @@
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   "position_embedding_type": "absolute",
   "torch_dtype": "float32",
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+  "transformers_version": "4.40.2",
   "type_vocab_size": 2,
   "use_cache": true,
   "vocab_size": 28996

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