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README.md

@@ -15,19 +15,32 @@ model-index:
 <!-- 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. -->
 
-# fine-tuned Deberta mdoel for climate claims verification task(using gold evidence)
+# out
 
-This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on climate claim verification training dataset(using gold evidence provided by the training set).
-It achieves the following results on the development set:
-- Loss: 0.8805
-- F1: 0.7383
-- Accuracy: 0.8117
+This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.9680
+- F1: 0.7035
+- Accuracy: 0.7857
 
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
 
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 2e-05
+- learning_rate: 1.5e-05
 - train_batch_size: 4
 - eval_batch_size: 4
 - seed: 42
@@ -42,21 +55,21 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:------:|:--------:|
-| 5.1051        | 1.0   | 77   | 1.2925          | 0.1910 | 0.3506   |
-| 4.7117        | 2.0   | 154  | 1.0855          | 0.3861 | 0.6429   |
-| 4.3050        | 3.0   | 231  | 1.0556          | 0.3987 | 0.6623   |
-| 3.5951        | 4.0   | 308  | 0.9764          | 0.6400 | 0.7662   |
-| 3.1353        | 5.0   | 385  | 0.8932          | 0.6145 | 0.7468   |
-| 2.6044        | 6.0   | 462  | 0.9282          | 0.6647 | 0.7662   |
-| 2.5715        | 7.0   | 539  | 0.8573          | 0.7067 | 0.7792   |
-| 2.1888        | 8.0   | 616  | 0.8713          | 0.6826 | 0.7792   |
-| 1.9936        | 9.0   | 693  | 0.8703          | 0.7249 | 0.8117   |
-| 1.8500        | 10.0  | 770  | 0.8805          | 0.7383 | 0.8117   |
+| 5.4135        | 1.0   | 77   | 1.3468          | 0.1532 | 0.4416   |
+| 4.6607        | 2.0   | 154  | 1.1471          | 0.3819 | 0.6364   |
+| 4.2591        | 3.0   | 231  | 1.1545          | 0.3801 | 0.6234   |
+| 3.9299        | 4.0   | 308  | 0.9857          | 0.6322 | 0.7013   |
+| 3.2692        | 5.0   | 385  | 0.8877          | 0.6500 | 0.7273   |
+| 2.7183        | 6.0   | 462  | 1.0321          | 0.6360 | 0.7403   |
+| 2.3779        | 7.0   | 539  | 0.9220          | 0.7017 | 0.7727   |
+| 2.1893        | 8.0   | 616  | 0.9742          | 0.7196 | 0.7922   |
+| 1.9169        | 9.0   | 693  | 0.9781          | 0.7034 | 0.7857   |
+| 1.8150        | 10.0  | 770  | 0.9680          | 0.7035 | 0.7857   |
 
 
 ### Framework versions
 
-- Transformers 5.9.0
+- Transformers 5.8.0
 - Pytorch 2.10.0+cu128
 - Datasets 4.8.5
 - Tokenizers 0.22.2

config.json

@@ -44,7 +44,7 @@
   "relative_attention": true,
   "share_att_key": true,
   "tie_word_embeddings": true,
-  "transformers_version": "5.9.0",
+  "transformers_version": "5.8.0",
   "type_vocab_size": 0,
   "use_cache": false,
   "vocab_size": 128100

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