update model card README.md

README.md

@@ -1,7 +1,89 @@
 ---
-widget:
-- text: "The.French.Movie.2013.720p.BluRay.x264.German-ROUGH[PublicHD]"
-  example_title: "Movie with language in title"
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- movie_releases
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: bert-finetuned-radarr
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: movie_releases
+      type: movie_releases
+      args: default
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.9555421444377389
+    - name: Recall
+      type: recall
+      value: 0.9638798701298701
+    - name: F1
+      type: f1
+      value: 0.9596928982725529
+    - name: Accuracy
+      type: accuracy
+      value: 0.9817602584524263
 ---
 
-Movie parser based on distilbert
+<!-- 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-finetuned-radarr
+
+This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the movie_releases dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0731
+- Precision: 0.9555
+- Recall: 0.9639
+- F1: 0.9597
+- Accuracy: 0.9818
+
+## 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: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.0431        | 1.0   | 1191 | 0.1403          | 0.9436    | 0.9574 | 0.9504 | 0.9626   |
+| 0.0236        | 2.0   | 2382 | 0.0881          | 0.9485    | 0.9560 | 0.9522 | 0.9694   |
+| 0.0138        | 3.0   | 3573 | 0.0731          | 0.9555    | 0.9639 | 0.9597 | 0.9818   |
+
+
+### Framework versions
+
+- Transformers 4.20.1
+- Pytorch 1.11.0+cu113
+- Datasets 2.3.2
+- Tokenizers 0.12.1