update model card README.md

README.md

@@ -0,0 +1,79 @@
+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- massive
+metrics:
+- accuracy
+model-index:
+- name: distilbert-base-uncased-finetuned-massive-intent-detection-english
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: massive
+      type: massive
+      args: en-US
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.886684599865501
+---
+
+<!-- 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-finetuned-massive-intent-detection-english
+
+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: 0.4873
+- Accuracy: 0.8867
+
+## 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: 32
+- eval_batch_size: 32
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 2.5849        | 1.0   | 360  | 1.3826          | 0.7359   |
+| 1.0662        | 2.0   | 720  | 0.7454          | 0.8357   |
+| 0.5947        | 3.0   | 1080 | 0.5668          | 0.8642   |
+| 0.3824        | 4.0   | 1440 | 0.5007          | 0.8770   |
+| 0.2649        | 5.0   | 1800 | 0.4829          | 0.8824   |
+| 0.1877        | 6.0   | 2160 | 0.4843          | 0.8824   |
+| 0.1377        | 7.0   | 2520 | 0.4858          | 0.8834   |
+| 0.1067        | 8.0   | 2880 | 0.4924          | 0.8864   |
+
+
+### Framework versions
+
+- Transformers 4.19.2
+- Pytorch 1.11.0+cu113
+- Datasets 2.2.2
+- Tokenizers 0.12.1