End of training

README.md

@@ -18,8 +18,8 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.9119
-- F1: 0.5990
+- Loss: 0.9208
+- F1: 0.6084
 
 ## Model description
 
@@ -42,21 +42,23 @@ The following hyperparameters were used during training:
 - train_batch_size: 16
 - eval_batch_size: 16
 - seed: 42
-- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- 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
-- num_epochs: 2
+- num_epochs: 4
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | F1     |
 |:-------------:|:-----:|:----:|:---------------:|:------:|
-| 1.0988        | 1.0   | 563  | 0.9617          | 0.5590 |
-| 0.8974        | 2.0   | 1126 | 0.9119          | 0.5990 |
+| 1.1018        | 1.0   | 563  | 0.9671          | 0.5583 |
+| 0.905         | 2.0   | 1126 | 0.9118          | 0.6050 |
+| 0.8162        | 3.0   | 1689 | 0.9101          | 0.6047 |
+| 0.7338        | 4.0   | 2252 | 0.9208          | 0.6084 |
 
 
 ### Framework versions
 
-- Transformers 4.46.3
-- Pytorch 2.5.1+cu121
-- Datasets 3.1.0
-- Tokenizers 0.20.3
+- Transformers 4.51.3
+- Pytorch 2.6.0+cu124
+- Datasets 3.5.0
+- Tokenizers 0.21.1

model.safetensors

@@ -1,3 +1,3 @@
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 size 267844872