add model

README.md

@@ -3,55 +3,54 @@ license: apache-2.0
 tags:
 - generated_from_keras_callback
 model-index:
-- name: tmp3y468_8j
+- name: tmpnhxhsble
   results: []
-widget:
-- text: "Ich liebe dich"
-  example_title: "Non-vulgar"
-- text: "Leck mich am arsch"
-  example_title: "Vulgar"
 ---
 
-# KIZervus
+<!-- This model card has been generated automatically according to the information Keras had access to. You should
+probably proofread and complete it, then remove this comment. -->
 
-This model is a fine-tuned version of [distilbert-base-german-cased](https://huggingface.co/distilbert-base-german-cased).
-It is trained to classify german text into the classes "vulgar" speech and "non-vulgar" speech. 
-The data set is a collection of other labeled sources in german. For an overview, see the github repository here: https://github.com/NKDataConv/KIZervus
-Both data and training procedure are documented in the GitHub repo. Your are welcome to contribute.
+# tmpnhxhsble
 
+This model is a fine-tuned version of [distilbert-base-german-cased](https://huggingface.co/distilbert-base-german-cased) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Train Loss: 0.4221
-- Train Accuracy: 0.8025
-- Validation Loss: 0.4418
-- Validation Accuracy: 0.8094
-- Epoch: 2
+- Train Loss: 0.4640
+- Train Accuracy: 0.7744
+- Validation Loss: 0.4852
+- Validation Accuracy: 0.7937
+- Epoch: 1
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
 
 ## Training procedure
-For details, see the repo and documentation here: https://github.com/NKDataConv/KIZervus
 
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- optimizer: {'name': 'Adam', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 5e-05, 'decay_steps': 1233, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
+- optimizer: {'name': 'Adam', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 5e-05, 'decay_steps': 822, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
 - training_precision: float32
 
 ### Training results
 
 | Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch |
 |:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
-| 0.4524     | 0.7813         | 0.4397          | 0.7969              | 0     |
-| 0.4215     | 0.8030         | 0.4838          | 0.7781              | 1     |
-| 0.4221     | 0.8025         | 0.4418          | 0.8094              | 2     |
+| 0.4830     | 0.7617         | 0.5061          | 0.7406              | 0     |
+| 0.4640     | 0.7744         | 0.4852          | 0.7937              | 1     |
 
 
 ### Framework versions
 
-- Transformers 4.21.1
+- Transformers 4.21.2
 - TensorFlow 2.8.2
 - Datasets 2.2.2
 - Tokenizers 0.12.1
-
-### Supporter
-
-![BMBF Logo](./BMBF_Logo.png)
-

config.json

@@ -19,6 +19,6 @@
   "seq_classif_dropout": 0.2,
   "sinusoidal_pos_embds": true,
   "tie_weights_": true,
-  "transformers_version": "4.21.1",
+  "transformers_version": "4.21.2",
   "vocab_size": 31102
 }

tf_model.h5

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:cb2593312c37ef57c22d2f93b17735ceb7c872234e17ed2134b73b98a3322e46
-size 269738152
+oid sha256:8362d35f35b804c48d5cd1381a5315ba84d22039e390a3cb7c3ae1bafa36498a
+size 269733656