add model

README.md

@@ -1,38 +1,47 @@
 ---
-language:
-- en
-license: lgpl-3.0
 tags:
-- text-classification
-- transformers
-- tf
-metrics:
-- accuracy
-- f1
-- precision
-- recall
-widget:
-- text: This pandemic has shown us clearly the vulgarity of our healthcare "system." Highest costs in the world, yet not enough nurses or doctors. Many millions uninsured, while insurance company profits soar. The struggle continues. Healthcare is a human right. Medicare for all.
-  example_title: "Bernie Sanders"
+- generated_from_keras_callback
+model-index:
+- name: distilbert-political-tweets
+  results: []
 ---
 
+<!-- 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. -->
+
 # distilbert-political-tweets
 
-*Note: model needs to be trained on more current data*
+This model was trained from scratch on an unknown dataset.
+It achieves the following results on the evaluation set:
+
+
+## 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:
+- optimizer: None
+- training_precision: float32
 
-🗣 🇺🇸 Classify sentiment as Democratic or Republican.
+### Training results
 
-# Model
 
-[DistilBERT base model (uncased)](https://huggingface.co/distilbert-base-uncased) for sequence classification fine-tuned on ~10,000 randomly selected tweets from Democratic and Republican senators from FiveThirtyEight's [twitter-ratio/senators](https://fivethirtyeight.datasettes.com/fivethirtyeight/twitter-ratio%2Fsenators#export) dataset.
 
-# Evaluation
+### Framework versions
 
-The model was evaluated on a validation dataset of ~3,000 unseen random tweets:
-```python
-{'eval_accuracy': 0.9348,
- 'eval_f1': 0.9386,
- 'eval_loss': 0.1975,
- 'eval_precision': 0.9281,
- 'eval_recall': 0.9494}
-```
+- Transformers 4.16.2
+- TensorFlow 2.8.0
+- Datasets 1.18.3
+- Tokenizers 0.11.6

config.json

@@ -1,5 +1,5 @@
 {
-  "_name_or_path": "/content/drive/MyDrive/ColabData/models/distilbert-political-tweets-model",
+  "_name_or_path": "/content/drive/MyDrive/colab_data/models/distilbert-political-tweets",
   "activation": "gelu",
   "architectures": [
     "DistilBertForSequenceClassification"
@@ -8,24 +8,18 @@
   "dim": 768,
   "dropout": 0.1,
   "hidden_dim": 3072,
-  "id2label": {
-    "0": "Democrat",
-    "1": "Republican"
-  },
   "initializer_range": 0.02,
-  "id2label": {
-    "0": "Democrat",
-    "1": "Republican"
-  },
   "max_position_embeddings": 512,
   "model_type": "distilbert",
   "n_heads": 12,
   "n_layers": 6,
   "pad_token_id": 0,
+  "problem_type": "single_label_classification",
   "qa_dropout": 0.1,
   "seq_classif_dropout": 0.2,
   "sinusoidal_pos_embds": false,
   "tie_weights_": true,
-  "transformers_version": "4.6.0",
+  "torch_dtype": "float32",
+  "transformers_version": "4.16.2",
   "vocab_size": 30522
 }

tf_model.h5

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
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-size 267951896
+oid sha256:f1d81f72c88328d81fe9e02483c71829ea44d09c8128b381daca374e05ed1dd9
+size 267956392