update model card README.md

README.md

@@ -4,28 +4,9 @@ tags:
 - generated_from_trainer
 datasets:
 - imdb
-metrics:
-- accuracy
-- f1
 model-index:
 - name: finetuning-sentiment-model-25000-samples
-  results:
-  - task:
-      name: Text Classification
-      type: text-classification
-    dataset:
-      name: imdb
-      type: imdb
-      config: plain_text
-      split: test
-      args: plain_text
-    metrics:
-    - name: Accuracy
-      type: accuracy
-      value: 0.93064
-    - name: F1
-      type: f1
-      value: 0.9309878213802436
+  results: []
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -35,9 +16,13 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the imdb dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.2450
-- Accuracy: 0.9306
-- F1: 0.9310
+- eval_loss: 0.2321
+- eval_accuracy: 0.932
+- eval_f1: 0.9327
+- eval_runtime: 421.5501
+- eval_samples_per_second: 59.305
+- eval_steps_per_second: 3.708
+- step: 0
 
 ## Model description
 
@@ -64,14 +49,6 @@ The following hyperparameters were used during training:
 - lr_scheduler_type: linear
 - num_epochs: 2
 
-### Training results
-
-| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
-|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
-| 0.2425        | 1.0   | 1563 | 0.1891          | 0.9269   | 0.9261 |
-| 0.1296        | 2.0   | 3126 | 0.2450          | 0.9306   | 0.9310 |
-
-
 ### Framework versions
 
 - Transformers 4.30.2