Update README.md

README.md

@@ -1,61 +1,68 @@
----
-library_name: transformers
-license: mit
-base_model: facebook/bart-large-mnli
-tags:
-- generated_from_keras_callback
-model-index:
-- name: zero-shot-prompt-classifier-bart-ft
-  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. -->
-
-# zero-shot-prompt-classifier-bart-ft
-
-This model is a fine-tuned version of [facebook/bart-large-mnli](https://huggingface.co/facebook/bart-large-mnli) on an unknown dataset.
-It achieves the following results on the evaluation set:
-- Train Loss: 0.4474
-- Train Accuracy: 0.7843
-- Validation Loss: 1.5942
-- Validation Accuracy: 0.4657
-- Epoch: 4
-
-## 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': False, 'is_legacy_optimizer': False, 'learning_rate': 5e-06, '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 |
-|:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
-| 0.9969     | 0.5490         | 0.9182          | 0.6225              | 0     |
-| 0.7647     | 0.6601         | 1.0025          | 0.5441              | 1     |
-| 0.6465     | 0.7157         | 1.1472          | 0.5392              | 2     |
-| 0.5849     | 0.7418         | 1.1974          | 0.5049              | 3     |
-| 0.4474     | 0.7843         | 1.5942          | 0.4657              | 4     |
-
-
-### Framework versions
-
-- Transformers 4.44.2
-- TensorFlow 2.18.0-dev20240717
-- Datasets 2.21.0
-- Tokenizers 0.19.1
+---
+library_name: transformers
+license: mit
+base_model: facebook/bart-large-mnli
+tags:
+- generated_from_keras_callback
+model-index:
+- name: zero-shot-prompt-classifier-bart-ft
+  results: []
+datasets:
+- reddgr/nli-chatbot-prompt-categorization
+---
+
+# zero-shot-prompt-classifier-bart-ft
+
+This model is a fine-tuned version of [facebook/bart-large-mnli](https://huggingface.co/facebook/bart-large-mnli) on the [reddgr/nli-chatbot-prompt-categorization](https://huggingface.co/datasets/reddgr/nli-chatbot-prompt-categorization) dataset.
+
+The purpose of the model is to help classify chatbot prompts into categories that are relevant in the context of working with LLM conversational tools: 
+coding assistance, language assistance, role play, creative writing, general knowledge questions... 
+
+The model is fine-tuned and tested on the natural language inference (NLI) dataset [reddgr/nli-chatbot-prompt-categorization](https://huggingface.co/datasets/reddgr/nli-chatbot-prompt-categorization)
+
+Below is a confusion matrix calculated on zero-shot inferences for the 10 most popular categories in the Test split of [reddgr/nli-chatbot-prompt-categorization](https://huggingface.co/datasets/reddgr/nli-chatbot-prompt-categorization) at the time of the first model upload:
+
+![Zero-shot prompt classification confusion matrix for reddgr/zero-shot-prompt-classifier-bart-ft](https://talkingtochatbots.com/wp-content/uploads/2024/12/NLI-prompt-classification.png)
+
+As of the first version of the model uploaded to hub, the fine-tuned version outperforms the base model [facebook/bart-large-mnli](https://huggingface.co/facebook/bart-large-mnli) by 8 percentage points in this test set with 10 candidate zero-shot classes (the most frequent categories in the test split of [reddgr/nli-chatbot-prompt-categorization](https://huggingface.co/datasets/reddgr/nli-chatbot-prompt-categorization) at the time of the first model upload.
+
+The dataset and the model are continously updated as they assist with content publishing on my website [Talking to Chatbots](https://talkingtochatbots) 
+
+
+## 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': False, 'is_legacy_optimizer': False, 'learning_rate': 5e-06, '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 |
+|:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
+| 0.9969     | 0.5490         | 0.9182          | 0.6225              | 0     |
+| 0.7647     | 0.6601         | 1.0025          | 0.5441              | 1     |
+| 0.6465     | 0.7157         | 1.1472          | 0.5392              | 2     |
+| 0.5849     | 0.7418         | 1.1974          | 0.5049              | 3     |
+| 0.4474     | 0.7843         | 1.5942          | 0.4657              | 4     |
+
+
+### Framework versions
+
+- Transformers 4.44.2
+- TensorFlow 2.18.0-dev20240717
+- Datasets 2.21.0
+- Tokenizers 0.19.1