End of training

README.md

@@ -15,7 +15,7 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [fahadqazi/testts1234](https://huggingface.co/fahadqazi/testts1234) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.3380
+- Loss: 0.3292
 
 ## Model description
 
@@ -34,30 +34,30 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 5e-05
+- learning_rate: 2.53e-05
 - train_batch_size: 64
 - eval_batch_size: 100
 - seed: 42
 - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
-- lr_scheduler_type: cosine
-- lr_scheduler_warmup_steps: 200
-- training_steps: 100
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 1000
+- training_steps: 5000
 - mixed_precision_training: Native AMP
 
 ### Training results
 
-| Training Loss | Epoch  | Step | Validation Loss |
-|:-------------:|:------:|:----:|:---------------:|
-| 0.3722        | 0.0385 | 10   | 0.3372          |
-| 0.3916        | 0.0769 | 20   | 0.3372          |
-| 0.3702        | 0.1154 | 30   | 0.3367          |
-| 0.3858        | 0.1538 | 40   | 0.3367          |
-| 0.3674        | 0.1923 | 50   | 0.3367          |
-| 0.3636        | 0.2308 | 60   | 0.3364          |
-| 0.3876        | 0.2692 | 70   | 0.3371          |
-| 0.3963        | 0.3077 | 80   | 0.3371          |
-| 0.3692        | 0.3462 | 90   | 0.3382          |
-| 0.3707        | 0.3846 | 100  | 0.3380          |
+| Training Loss | Epoch   | Step | Validation Loss |
+|:-------------:|:-------:|:----:|:---------------:|
+| 0.3551        | 1.9231  | 500  | 0.3307          |
+| 0.3621        | 3.8462  | 1000 | 0.3360          |
+| 0.363         | 5.7692  | 1500 | 0.3327          |
+| 0.3637        | 7.6923  | 2000 | 0.3326          |
+| 0.3606        | 9.6154  | 2500 | 0.3314          |
+| 0.3595        | 11.5385 | 3000 | 0.3306          |
+| 0.3594        | 13.4615 | 3500 | 0.3307          |
+| 0.3594        | 15.3846 | 4000 | 0.3296          |
+| 0.3602        | 17.3077 | 4500 | 0.3294          |
+| 0.3577        | 19.2308 | 5000 | 0.3292          |
 
 
 ### Framework versions