Training completed!

README.md

@@ -0,0 +1,88 @@
+---
+license: apache-2.0
+base_model: distilbert-base-uncased
+tags:
+- generated_from_trainer
+datasets:
+- emotion
+metrics:
+- accuracy
+- f1
+- precision
+model-index:
+- name: distilbert-base-uncased_emotion_ft_0416
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: emotion
+      type: emotion
+      config: split
+      split: validation
+      args: split
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.9355
+    - name: F1
+      type: f1
+      value: 0.9354663445630791
+    - name: Precision
+      type: precision
+      value: 0.9083088769303077
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# distilbert-base-uncased_emotion_ft_0416
+
+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: 0.1489
+- Accuracy: 0.9355
+- F1: 0.9355
+- Precision: 0.9083
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 2e-05
+- 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: 4
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|
+| 0.7697        | 1.0   | 250  | 0.2589          | 0.9215   | 0.9218 | 0.8905    |
+| 0.2077        | 2.0   | 500  | 0.1735          | 0.929    | 0.9293 | 0.9003    |
+| 0.1397        | 3.0   | 750  | 0.1531          | 0.934    | 0.9346 | 0.8979    |
+| 0.1136        | 4.0   | 1000 | 0.1489          | 0.9355   | 0.9355 | 0.9083    |
+
+
+### Framework versions
+
+- Transformers 4.39.1
+- Pytorch 2.2.1+cu121
+- Datasets 2.19.0
+- Tokenizers 0.15.2

config.json

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   "sinusoidal_pos_embds": false,
   "tie_weights_": true,
   "torch_dtype": "float32",
-  "transformers_version": "4.37.2",
+  "transformers_version": "4.39.1",
   "vocab_size": 30522
 }

model.safetensors

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runs/Apr20_20-19-44_tim-PowerEdge-T640/events.out.tfevents.1713615592.tim-PowerEdge-T640.321149.0

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tokenizer.json

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 {
   "version": "1.0",
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-  "padding": null,
+  "truncation": {
+    "direction": "Right",
+    "max_length": 512,
+    "strategy": "LongestFirst",
+    "stride": 0
+  },
+  "padding": {
+    "strategy": "BatchLongest",
+    "direction": "Right",
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+    "pad_id": 0,
+    "pad_type_id": 0,
+    "pad_token": "[PAD]"
+  },
   "added_tokens": [
     {
       "id": 0,

training_args.bin

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