Training completed!

README.md

@@ -4,9 +4,6 @@ license: apache-2.0
 base_model: distilbert-base-uncased
 tags:
 - generated_from_trainer
-metrics:
-- accuracy
-- f1
 model-index:
 - name: distilbert-base-uncased-finetuned-emotion
   results: []
@@ -18,10 +15,6 @@ should probably proofread and complete it, then remove this comment. -->
 # distilbert-base-uncased-finetuned-emotion
 
 This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.2096
-- Accuracy: 0.925
-- F1: 0.9249
 
 ## Model description
 
@@ -44,21 +37,13 @@ The following hyperparameters were used during training:
 - train_batch_size: 64
 - eval_batch_size: 64
 - seed: 42
-- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- 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
 
-### Training results
-
-| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
-|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
-| 0.8021        | 1.0   | 250  | 0.2950          | 0.91     | 0.9096 |
-| 0.2381        | 2.0   | 500  | 0.2096          | 0.925    | 0.9249 |
-
-
 ### Framework versions
 
-- Transformers 4.44.2
-- Pytorch 2.4.1+cu121
-- Datasets 3.0.1
-- Tokenizers 0.19.1
+- Transformers 4.48.3
+- Pytorch 2.5.1+cu124
+- Datasets 3.3.2
+- Tokenizers 0.21.0

runs/Feb20_21-27-11_bc554d6b7727/events.out.tfevents.1740086833.bc554d6b7727.2871.0

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