End of training

README.md

@@ -1,7 +1,7 @@
 ---
 library_name: transformers
 license: apache-2.0
-base_model: bert-base-uncased
+base_model: distilbert/distilbert-base-uncased
 tags:
 - generated_from_trainer
 metrics:
@@ -17,11 +17,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 # classifier-chapter4
 
-This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
+This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.2447
-- Accuracy: 0.9225
-- F1: 0.9225
+- Loss: 0.2417
+- Accuracy: 0.9197
+- F1: 0.9198
 
 ## Model description
 
@@ -44,7 +44,7 @@ The following hyperparameters were used during training:
 - train_batch_size: 32
 - eval_batch_size: 32
 - seed: 42
-- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - num_epochs: 2
 
@@ -52,13 +52,13 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
-| No log        | 1.0   | 313  | 0.2626          | 0.9104   | 0.9101 |
-| 0.2954        | 2.0   | 626  | 0.2447          | 0.9225   | 0.9225 |
+| No log        | 1.0   | 313  | 0.2637          | 0.9137   | 0.9135 |
+| 0.3064        | 2.0   | 626  | 0.2417          | 0.9197   | 0.9198 |
 
 
 ### Framework versions
 
-- Transformers 4.46.3
+- Transformers 4.45.2
 - Pytorch 2.5.1
-- Datasets 2.16.1
-- Tokenizers 0.20.3
+- Datasets 3.1.0
+- Tokenizers 0.20.1