End of training

README.md

@@ -20,11 +20,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [google/muril-base-cased](https://huggingface.co/google/muril-base-cased) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.1230
-- Precision: 0.6712
-- Recall: 0.5389
-- F1: 0.5978
-- Accuracy: 0.9778
+- Loss: 0.0831
+- Precision: 0.7350
+- Recall: 0.7591
+- F1: 0.7469
+- Accuracy: 0.9843
 
 ## Model description
 
@@ -49,20 +49,22 @@ 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: 3
+- num_epochs: 5
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| 0.3756        | 1.0   | 1613 | 0.2888          | 0.0       | 0.0    | 0.0    | 0.9551   |
-| 0.1773        | 2.0   | 3226 | 0.1430          | 0.6314    | 0.4846 | 0.5484 | 0.9749   |
-| 0.1247        | 3.0   | 4839 | 0.1230          | 0.6712    | 0.5389 | 0.5978 | 0.9778   |
+| 0.3465        | 1.0   | 1613 | 0.2747          | 0.0       | 0.0    | 0.0    | 0.9551   |
+| 0.1642        | 2.0   | 3226 | 0.1273          | 0.6436    | 0.5216 | 0.5762 | 0.9758   |
+| 0.1053        | 3.0   | 4839 | 0.0986          | 0.7257    | 0.7156 | 0.7206 | 0.9824   |
+| 0.0863        | 4.0   | 6452 | 0.0854          | 0.7166    | 0.7620 | 0.7386 | 0.9837   |
+| 0.0705        | 5.0   | 8065 | 0.0831          | 0.7350    | 0.7591 | 0.7469 | 0.9843   |
 
 
 ### Framework versions
 
-- Transformers 4.34.0
-- Pytorch 2.0.1+cu118
+- Transformers 4.33.0
+- Pytorch 2.0.0
 - Datasets 2.14.5
-- Tokenizers 0.14.0
+- Tokenizers 0.13.3

config.json

@@ -37,7 +37,7 @@
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   "position_embedding_type": "absolute",
   "torch_dtype": "float32",
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+  "transformers_version": "4.33.0",
   "type_vocab_size": 2,
   "use_cache": true,
   "vocab_size": 197285

pytorch_model.bin

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tokenizer_config.json

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   "cls_token": "[CLS]",
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training_args.bin

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