End of training

README.md

@@ -19,9 +19,9 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.6234
-- Accuracy: 0.9414
-- F1: 0.9411
+- Loss: 1.1409
+- Accuracy: 0.7115
+- F1: 0.7184
 
 ## Model description
 
@@ -40,38 +40,34 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 8e-05
-- train_batch_size: 192
-- eval_batch_size: 192
+- learning_rate: 5e-05
+- train_batch_size: 256
+- eval_batch_size: 256
 - seed: 42
 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
 - lr_scheduler_type: linear
-- lr_scheduler_warmup_ratio: 0.08
+- lr_scheduler_warmup_ratio: 0.1
 - num_epochs: 5
 
 ### Training results
 
 | Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1     |
 |:-------------:|:------:|:----:|:---------------:|:--------:|:------:|
-| 1.7318        | 0.2591 | 100  | 0.8266          | 0.6828   | 0.7221 |
-| 0.8015        | 0.5181 | 200  | 0.5297          | 0.8188   | 0.8271 |
-| 0.6969        | 0.7772 | 300  | 0.4705          | 0.8342   | 0.8482 |
-| 0.5794        | 1.0363 | 400  | 0.4594          | 0.8686   | 0.8714 |
-| 0.4761        | 1.2953 | 500  | 0.4386          | 0.8736   | 0.8777 |
-| 0.4406        | 1.5544 | 600  | 0.4049          | 0.8858   | 0.8874 |
-| 0.4279        | 1.8135 | 700  | 0.4328          | 0.8955   | 0.8965 |
-| 0.4206        | 2.0725 | 800  | 0.4511          | 0.9006   | 0.9011 |
-| 0.2375        | 2.3316 | 900  | 0.4064          | 0.9018   | 0.9034 |
-| 0.1855        | 2.5907 | 1000 | 0.4421          | 0.9099   | 0.9109 |
-| 0.1951        | 2.8497 | 1100 | 0.3979          | 0.9140   | 0.9150 |
-| 0.1464        | 3.1088 | 1200 | 0.5462          | 0.9253   | 0.9253 |
-| 0.0533        | 3.3679 | 1300 | 0.5703          | 0.9313   | 0.9314 |
-| 0.0508        | 3.6269 | 1400 | 0.5185          | 0.9343   | 0.9342 |
-| 0.0488        | 3.8860 | 1500 | 0.5403          | 0.9378   | 0.9375 |
-| 0.0268        | 4.1451 | 1600 | 0.5958          | 0.9399   | 0.9396 |
-| 0.007         | 4.4041 | 1700 | 0.5955          | 0.9379   | 0.9377 |
-| 0.0052        | 4.6632 | 1800 | 0.6330          | 0.9400   | 0.9397 |
-| 0.0049        | 4.9223 | 1900 | 0.6234          | 0.9414   | 0.9411 |
+| 5.0513        | 0.3333 | 226  | 4.6666          | 0.0150   | 0.0139 |
+| 2.9839        | 0.6667 | 452  | 2.4637          | 0.2933   | 0.3601 |
+| 2.0766        | 1.0    | 678  | 1.8938          | 0.4410   | 0.5005 |
+| 1.5464        | 1.3333 | 904  | 1.6542          | 0.4547   | 0.5265 |
+| 1.4301        | 1.6667 | 1130 | 1.4822          | 0.4976   | 0.5625 |
+| 1.2864        | 2.0    | 1356 | 1.3587          | 0.4388   | 0.5155 |
+| 0.7659        | 2.3333 | 1582 | 1.2553          | 0.5637   | 0.6038 |
+| 0.7489        | 2.6667 | 1808 | 1.1776          | 0.5639   | 0.6072 |
+| 0.658         | 3.0    | 2034 | 1.1178          | 0.5851   | 0.6249 |
+| 0.3545        | 3.3333 | 2260 | 1.0968          | 0.6086   | 0.6372 |
+| 0.3468        | 3.6667 | 2486 | 1.1013          | 0.6502   | 0.6693 |
+| 0.3072        | 4.0    | 2712 | 1.0774          | 0.6637   | 0.6816 |
+| 0.1741        | 4.3333 | 2938 | 1.1204          | 0.6946   | 0.7043 |
+| 0.1531        | 4.6667 | 3164 | 1.1361          | 0.7065   | 0.7134 |
+| 0.1556        | 5.0    | 3390 | 1.1409          | 0.7115   | 0.7184 |
 
 
 ### Framework versions