update model card README.md

README.md

@@ -1,5 +1,5 @@
 ---
-license: apache-2.0
+license: mit
 tags:
 - generated_from_trainer
 datasets:
@@ -21,7 +21,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.9435
+      value: 0.947
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -29,10 +29,10 @@ should probably proofread and complete it, then remove this comment. -->
 
 # jq_emo_gpt
 
-This model is a fine-tuned version of [distilgpt2](https://huggingface.co/distilgpt2) on the emotion dataset.
+This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the emotion dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.2417
-- Accuracy: 0.9435
+- Loss: 0.2536
+- Accuracy: 0.947
 
 ## Model description
 
@@ -57,14 +57,17 @@ The following hyperparameters were used during training:
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- lr_scheduler_warmup_steps: 1600
-- num_epochs: 1
+- lr_scheduler_warmup_steps: 6400
+- num_epochs: 4
 
 ### Training results
 
 | Training Loss | Epoch | Step  | Validation Loss | Accuracy |
 |:-------------:|:-----:|:-----:|:---------------:|:--------:|
-| 0.2402        | 1.0   | 16000 | 0.2417          | 0.9435   |
+| 0.5109        | 1.0   | 16000 | 0.5014          | 0.929    |
+| 0.3765        | 2.0   | 32000 | 0.3135          | 0.9385   |
+| 0.2526        | 3.0   | 48000 | 0.2385          | 0.945    |
+| 0.1952        | 4.0   | 64000 | 0.2536          | 0.947    |
 
 
 ### Framework versions