Upload TFDistilBertForSequenceClassification

README.md

@@ -1,12 +1,62 @@
 ---
+library_name: transformers
 license: apache-2.0
-base_model:
-- distilbert/distilbert-base-uncased
+base_model: distilbert-base-uncased
 tags:
-- text-classification
-- chatbot-prompts
+- generated_from_keras_callback
+model-index:
+- name: tl-test-learn-prompt-classifier
+  results: []
 ---
 
-This is a fine-tuning of [distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) trained on a small set of manually labeled sentences classified as "instruction" or "problem". 
-The main purpose is to calculate metrics used by the SCBN-RQTL chatbot response evaluation benchmark. The acronym TL stands for Test vs. Learn and is based on the assumption that prompts labeled as 'instruction' typically reflect the user's intent to 'learn,' while prompts labeled as 'problem' are generally aimed at 'testing' the chatbot by challenging it. 
-More information in the GitHub repository [here](https://github.com/reddgr/chatbot-response-scoring-scbn-rqtl)
+<!-- 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. -->
+
+# tl-test-learn-prompt-classifier
+
+This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Train Loss: 0.0794
+- Train Accuracy: 1.0
+- Validation Loss: 0.2381
+- Validation Accuracy: 0.9444
+- Epoch: 5
+
+## 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: {'name': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': 1e-05, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
+- training_precision: float32
+
+### Training results
+
+| Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch |
+|:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
+| 0.6829     | 0.5808         | 0.6541          | 0.7639              | 0     |
+| 0.6315     | 0.7784         | 0.5824          | 0.8472              | 1     |
+| 0.4975     | 0.9222         | 0.4382          | 0.8889              | 2     |
+| 0.3094     | 0.9521         | 0.3303          | 0.9028              | 3     |
+| 0.1684     | 0.9820         | 0.2741          | 0.9028              | 4     |
+| 0.0794     | 1.0            | 0.2381          | 0.9444              | 5     |
+
+
+### Framework versions
+
+- Transformers 4.46.2
+- TensorFlow 2.17.1
+- Datasets 3.1.0
+- Tokenizers 0.20.3

config.json

@@ -1,23 +1,23 @@
-{
-  "_name_or_path": "distilbert-base-uncased",
-  "activation": "gelu",
-  "architectures": [
-    "DistilBertForSequenceClassification"
-  ],
-  "attention_dropout": 0.1,
-  "dim": 768,
-  "dropout": 0.1,
-  "hidden_dim": 3072,
-  "initializer_range": 0.02,
-  "max_position_embeddings": 512,
-  "model_type": "distilbert",
-  "n_heads": 12,
-  "n_layers": 6,
-  "pad_token_id": 0,
-  "qa_dropout": 0.1,
-  "seq_classif_dropout": 0.2,
-  "sinusoidal_pos_embds": false,
-  "tie_weights_": true,
-  "transformers_version": "4.43.3",
-  "vocab_size": 30522
-}
+{
+  "_name_or_path": "distilbert-base-uncased",
+  "activation": "gelu",
+  "architectures": [
+    "DistilBertForSequenceClassification"
+  ],
+  "attention_dropout": 0.1,
+  "dim": 768,
+  "dropout": 0.1,
+  "hidden_dim": 3072,
+  "initializer_range": 0.02,
+  "max_position_embeddings": 512,
+  "model_type": "distilbert",
+  "n_heads": 12,
+  "n_layers": 6,
+  "pad_token_id": 0,
+  "qa_dropout": 0.1,
+  "seq_classif_dropout": 0.2,
+  "sinusoidal_pos_embds": false,
+  "tie_weights_": true,
+  "transformers_version": "4.46.2",
+  "vocab_size": 30522
+}

tf_model.h5

@@ -1,3 +1,3 @@
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