End of training

README.md

@@ -3,11 +3,6 @@ license: mit
 base_model: microsoft/deberta-v3-small
 tags:
 - generated_from_trainer
-metrics:
-- precision
-- recall
-- accuracy
-- f1
 model-index:
 - name: deberta-v3-ft-news-sentiment-analisys
   results: []
@@ -19,12 +14,6 @@ should probably proofread and complete it, then remove this comment. -->
 # deberta-v3-ft-news-sentiment-analisys
 
 This model is a fine-tuned version of [microsoft/deberta-v3-small](https://huggingface.co/microsoft/deberta-v3-small) on an unknown dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.2868
-- Precision: 0.8987
-- Recall: 0.8987
-- Accuracy: 0.8987
-- F1: 0.8987
 
 ## Model description
 
@@ -49,18 +38,7 @@ 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: 5
-
-### Training results
-
-| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | Accuracy | F1     |
-|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:--------:|:------:|
-| No log        | 1.0   | 64   | 0.8396          | 0.7093    | 0.7093 | 0.7093   | 0.7093 |
-| No log        | 2.0   | 128  | 0.4040          | 0.8194    | 0.8194 | 0.8194   | 0.8194 |
-| No log        | 3.0   | 192  | 0.4036          | 0.8238    | 0.8238 | 0.8238   | 0.8238 |
-| No log        | 4.0   | 256  | 0.3208          | 0.8767    | 0.8767 | 0.8767   | 0.8767 |
-| No log        | 5.0   | 320  | 0.2868          | 0.8987    | 0.8987 | 0.8987   | 0.8987 |
-
+- num_epochs: 10
 
 ### Framework versions
 

config.json

@@ -10,90 +10,14 @@
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   "layer_norm_eps": 1e-07,
   "max_position_embeddings": 512,

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