End of training

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- massive
+metrics:
+- accuracy
+model-index:
+- name: BERT-tiny-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: 0.8475159862272503
+---
+
+<!-- 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. -->
+
+# BERT-tiny-Massive-intent
+
+This model is a fine-tuned version of [google/bert_uncased_L-2_H-128_A-2](https://huggingface.co/google/bert_uncased_L-2_H-128_A-2) on the massive dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6740
+- Accuracy: 0.8475
+
+## 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: 50
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|
+| 3.6104        | 1.0   | 720   | 3.0911          | 0.3601   |
+| 2.8025        | 2.0   | 1440  | 2.3800          | 0.5165   |
+| 2.2292        | 3.0   | 2160  | 1.9134          | 0.5991   |
+| 1.818         | 4.0   | 2880  | 1.5810          | 0.6744   |
+| 1.5171        | 5.0   | 3600  | 1.3522          | 0.7108   |
+| 1.2876        | 6.0   | 4320  | 1.1686          | 0.7442   |
+| 1.1049        | 7.0   | 5040  | 1.0355          | 0.7683   |
+| 0.9623        | 8.0   | 5760  | 0.9466          | 0.7885   |
+| 0.8424        | 9.0   | 6480  | 0.8718          | 0.7875   |
+| 0.7473        | 10.0  | 7200  | 0.8107          | 0.8028   |
+| 0.6735        | 11.0  | 7920  | 0.7710          | 0.8180   |
+| 0.6085        | 12.0  | 8640  | 0.7404          | 0.8210   |
+| 0.5536        | 13.0  | 9360  | 0.7180          | 0.8229   |
+| 0.5026        | 14.0  | 10080 | 0.6980          | 0.8318   |
+| 0.4652        | 15.0  | 10800 | 0.6970          | 0.8337   |
+| 0.4234        | 16.0  | 11520 | 0.6822          | 0.8372   |
+| 0.3987        | 17.0  | 12240 | 0.6691          | 0.8436   |
+| 0.3707        | 18.0  | 12960 | 0.6679          | 0.8455   |
+| 0.3433        | 19.0  | 13680 | 0.6740          | 0.8475   |
+| 0.3206        | 20.0  | 14400 | 0.6760          | 0.8451   |
+| 0.308         | 21.0  | 15120 | 0.6704          | 0.8436   |
+| 0.2813        | 22.0  | 15840 | 0.6701          | 0.8416   |
+
+
+### Framework versions
+
+- Transformers 4.22.1
+- Pytorch 1.12.1+cu113
+- Datasets 2.5.1
+- Tokenizers 0.12.1

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