Model save

README.md

@@ -21,13 +21,13 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [MoritzLaurer/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7](https://huggingface.co/MoritzLaurer/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.8424
-- Model Preparation Time: 0.0068
-- Accuracy: 0.6173
-- Precision: 0.6539
-- Recall: 0.5487
-- F1: 0.5668
-- Ratio: 0.4136
+- Loss: 0.9601
+- Model Preparation Time: 0.0101
+- Accuracy: 0.6358
+- Precision: 0.6154
+- Recall: 0.6254
+- F1: 0.6161
+- Ratio: 0.4969
 
 ## Model description
 
@@ -50,18 +50,15 @@ The following hyperparameters were used during training:
 - train_batch_size: 8
 - eval_batch_size: 8
 - seed: 42
-- gradient_accumulation_steps: 2
-- total_train_batch_size: 16
 - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
 - lr_scheduler_type: linear
 - num_epochs: 1
-- mixed_precision_training: Native AMP
 
 ### Training results
 
-| Training Loss | Epoch  | Step | Validation Loss | Model Preparation Time | Accuracy | Precision | Recall | F1     | Ratio  |
-|:-------------:|:------:|:----:|:---------------:|:----------------------:|:--------:|:---------:|:------:|:------:|:------:|
-| No log        | 0.9895 | 47   | 0.8424          | 0.0068                 | 0.6173   | 0.6539    | 0.5487 | 0.5668 | 0.4136 |
+| Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Accuracy | Precision | Recall | F1     | Ratio  |
+|:-------------:|:-----:|:----:|:---------------:|:----------------------:|:--------:|:---------:|:------:|:------:|:------:|
+| No log        | 1.0   | 95   | 0.9601          | 0.0101                 | 0.6358   | 0.6154    | 0.6254 | 0.6161 | 0.4969 |
 
 
 ### Framework versions