End of training

README.md

@@ -1,6 +1,6 @@
 ---
 license: apache-2.0
-base_model: distilbert-base-cased
+base_model: distilbert-base-uncased
 tags:
 - generated_from_trainer
 metrics:
@@ -18,13 +18,13 @@ should probably proofread and complete it, then remove this comment. -->
 
 # trainer3
 
-This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on the None dataset.
+This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.0000
-- Precision: 1.0
-- Recall: 1.0
-- F1: 1.0
-- Accuracy: 1.0
+- Loss: 0.7977
+- Precision: 0.8653
+- Recall: 0.8624
+- F1: 0.8621
+- Accuracy: 0.8624
 
 ## Model description
 
@@ -44,39 +44,20 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 5e-05
-- train_batch_size: 8
-- eval_batch_size: 8
+- train_batch_size: 64
+- eval_batch_size: 64
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 10
+- num_epochs: 20
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1  | Accuracy |
-|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:---:|:--------:|
-| 0.0053        | 0.57  | 30   | 0.0010          | 1.0       | 1.0    | 1.0 | 1.0      |
-| 0.0011        | 1.13  | 60   | 0.0004          | 1.0       | 1.0    | 1.0 | 1.0      |
-| 0.0006        | 1.7   | 90   | 0.0003          | 1.0       | 1.0    | 1.0 | 1.0      |
-| 0.0004        | 2.26  | 120  | 0.0002          | 1.0       | 1.0    | 1.0 | 1.0      |
-| 0.0003        | 2.83  | 150  | 0.0001          | 1.0       | 1.0    | 1.0 | 1.0      |
-| 0.0002        | 3.4   | 180  | 0.0001          | 1.0       | 1.0    | 1.0 | 1.0      |
-| 0.0002        | 3.96  | 210  | 0.0001          | 1.0       | 1.0    | 1.0 | 1.0      |
-| 0.0002        | 4.53  | 240  | 0.0001          | 1.0       | 1.0    | 1.0 | 1.0      |
-| 0.0001        | 5.09  | 270  | 0.0001          | 1.0       | 1.0    | 1.0 | 1.0      |
-| 0.0001        | 5.66  | 300  | 0.0001          | 1.0       | 1.0    | 1.0 | 1.0      |
-| 0.0001        | 6.23  | 330  | 0.0001          | 1.0       | 1.0    | 1.0 | 1.0      |
-| 0.0001        | 6.79  | 360  | 0.0001          | 1.0       | 1.0    | 1.0 | 1.0      |
-| 0.0001        | 7.36  | 390  | 0.0000          | 1.0       | 1.0    | 1.0 | 1.0      |
-| 0.0001        | 7.92  | 420  | 0.0000          | 1.0       | 1.0    | 1.0 | 1.0      |
-| 0.0001        | 8.49  | 450  | 0.0000          | 1.0       | 1.0    | 1.0 | 1.0      |
-| 0.0001        | 9.06  | 480  | 0.0000          | 1.0       | 1.0    | 1.0 | 1.0      |
-| 0.0001        | 9.62  | 510  | 0.0000          | 1.0       | 1.0    | 1.0 | 1.0      |
 
 
 ### Framework versions
 
-- Transformers 4.38.2
+- Transformers 4.39.3
 - Pytorch 2.2.1+cu121
 - Datasets 2.18.0
 - Tokenizers 0.15.2

runs/Apr17_19-30-29_ee976d1206e9/events.out.tfevents.1713382940.ee976d1206e9.1226.5

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+size 560