End of training

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- massive
+metrics:
+- accuracy
+model-index:
+- name: distilbert-base-Massive-intent
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: massive
+      type: massive
+      config: en-US
+      split: train
+      args: en-US
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.8947368421052632
+---
+
+<!-- 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-Massive-intent
+
+This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the massive dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.7693
+- Accuracy: 0.8947
+
+## 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: 5e-05
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 33
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 15
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 1.4555        | 1.0   | 720  | 0.5983          | 0.8426   |
+| 0.407         | 2.0   | 1440 | 0.4702          | 0.8775   |
+| 0.2095        | 3.0   | 2160 | 0.5319          | 0.8834   |
+| 0.1172        | 4.0   | 2880 | 0.5902          | 0.8810   |
+| 0.0683        | 5.0   | 3600 | 0.6555          | 0.8810   |
+| 0.042         | 6.0   | 4320 | 0.6989          | 0.8879   |
+| 0.0253        | 7.0   | 5040 | 0.6963          | 0.8928   |
+| 0.0208        | 8.0   | 5760 | 0.7313          | 0.8908   |
+| 0.0119        | 9.0   | 6480 | 0.7683          | 0.8923   |
+| 0.0093        | 10.0  | 7200 | 0.7693          | 0.8947   |
+| 0.0071        | 11.0  | 7920 | 0.7873          | 0.8923   |
+| 0.0047        | 12.0  | 8640 | 0.8275          | 0.8893   |
+| 0.003         | 13.0  | 9360 | 0.8312          | 0.8928   |
+
+
+### Framework versions
+
+- Transformers 4.22.1
+- Pytorch 1.12.1+cu113
+- Datasets 2.5.1
+- Tokenizers 0.12.1

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