Training completed!

README.md

@@ -23,10 +23,10 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.9235
+      value: 0.8945
     - name: F1
       type: f1
-      value: 0.9231534611856926
+      value: 0.8905629739592735
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -36,9 +36,9 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the emotion dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.2196
-- Accuracy: 0.9235
-- F1: 0.9232
+- Loss: 0.3513
+- Accuracy: 0.8945
+- F1: 0.8906
 
 ## Model description
 
@@ -58,8 +58,8 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 2e-05
-- train_batch_size: 64
-- eval_batch_size: 64
+- train_batch_size: 128
+- eval_batch_size: 128
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
@@ -69,13 +69,13 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
-| 0.8302        | 1.0   | 250  | 0.3188          | 0.901    | 0.9002 |
-| 0.2473        | 2.0   | 500  | 0.2196          | 0.9235   | 0.9232 |
+| No log        | 1.0   | 125  | 0.5315          | 0.8495   | 0.8357 |
+| 0.7527        | 2.0   | 250  | 0.3513          | 0.8945   | 0.8906 |
 
 
 ### Framework versions
 
-- Transformers 4.41.1
-- Pytorch 2.3.0+cu121
-- Datasets 2.19.1
-- Tokenizers 0.19.1
+- Transformers 4.39.3
+- Pytorch 2.1.2
+- Datasets 2.18.0
+- Tokenizers 0.15.2

config.json

@@ -36,6 +36,6 @@
   "sinusoidal_pos_embds": false,
   "tie_weights_": true,
   "torch_dtype": "float32",
-  "transformers_version": "4.41.1",
+  "transformers_version": "4.39.3",
   "vocab_size": 30522
 }

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training_args.bin

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