Model save

README.md

@@ -1,32 +1,39 @@
----
-language:
-- en
-license: mit
-library_name: peft
-tags:
-- generated_from_trainer
-base_model: openai-community/gpt2
-datasets:
-- dair-ai/emotion
-metrics:
-- accuracy
-widget:
-- text: I liked this movie
-pipeline_tag: text-classification
-model-index:
-- name: emotion-gpt2-lora
-  results: []
----
+---
+license: mit
+library_name: peft
+tags:
+- generated_from_trainer
+base_model: openai-community/gpt2
+datasets:
+- emotion
+metrics:
+- accuracy
+model-index:
+- name: emotion-gpt2-lora
+  results: []
+---
 
 <!-- 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. -->
 
 # emotion-gpt2-lora
 
-This model is a fine-tuned version of [openai-community/gpt2](https://huggingface.co/openai-community/gpt2) on the fantastic Dair AI emotion dataset.
+This model is a fine-tuned version of [openai-community/gpt2](https://huggingface.co/openai-community/gpt2) on the emotion dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.1494
-- Accuracy: 0.939
+- Loss: 0.1395
+- Accuracy: 0.9345
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
 
 ## Training procedure
 
@@ -45,9 +52,9 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 0.7467        | 1.0   | 500  | 0.2384          | 0.914    |
-| 0.2357        | 2.0   | 1000 | 0.1689          | 0.9365   |
-| 0.1786        | 3.0   | 1500 | 0.1494          | 0.939    |
+| 0.7977        | 1.0   | 500  | 0.2264          | 0.9195   |
+| 0.234         | 2.0   | 1000 | 0.1599          | 0.932    |
+| 0.1773        | 3.0   | 1500 | 0.1395          | 0.9345   |
 
 
 ### Framework versions