diff --git a/.gitignore b/.gitignore
index 0fcc73c..1e5475d 100644
--- a/.gitignore
+++ b/.gitignore
@@ -1,3 +1,4 @@
 rasa-demo
 results.json
 report_main.json
+.history
\ No newline at end of file
diff --git a/README.md b/README.md
index 15f8d79..f5602fa 100644
--- a/README.md
+++ b/README.md
@@ -32,6 +32,7 @@ jobs:
 | `data_validate`      | Validates domain and data files to check for possible mistakes                | `true`                    |
 | `data_validate_args` | Additional arguments passed to the `rasa data validate` command               | `none`                    |
 | `fine_tune`          | Fine-tune an existing model with new training dataset                         | `false`                   |
+| `fixed_model_name`   | Name of the model file will be set to the given name                          | `none`                    |
 | `workspace`          | The root directory containing your Rasa Open Source project                   | `${{ github.workspace }}` |
 | `train_type`         | The types of training (available types: `core`/`nlu`/`all`)                   | `all`                     |
 | `train_args`         | Additional arguments passed to the `rasa train` command                       | `none`                    |
diff --git a/action.yml b/action.yml
index 25a4257..ab30702 100644
--- a/action.yml
+++ b/action.yml
@@ -21,6 +21,10 @@ inputs:
     description: 'Fine-tune model'
     required: false
     default: 'false'
+  fixed_model_name:
+    description: 'Name to be given to the model file'
+    required: false
+    default: ''
   data_validate:
     description: 'Validates domain and data files to check for possible mistakes'
     required: true
@@ -159,6 +163,11 @@ runs:
           echo MODEL_ARGS="--model /app/${{ inputs.model }}" >> $GITHUB_ENV
         fi
 
+        # Set a fixed model name
+        if [[ -n "${{ inputs.fixed_model_name }}" ]];then
+          echo FIXED_MODEL_ARGS="--fixed-model-name ${{ inputs.fixed_model_name }}" >> $GITHUB_ENV
+        fi
+
         # Set cross validation
         if [[ "${{ inputs.cross_validation }}" == "true" ]];then
           echo CROSS_VALIDATION_ARGS="--cross-validation" >> $GITHUB_ENV
@@ -240,7 +249,7 @@ runs:
         elif [[ "${{ inputs.rasa_train }}" == "true" ]]; then
           echo "Run the rasa train"
           echo ""
-          docker run ${{ env.DOCKER_ARGS }} ${{ env.RASA_IMAGE }} train ${{ env.TRAIN_TYPE }} ${{ env.DEFAULT_ARGS }} ${{ env.FINE_TUNE }} ${{ inputs.train_args }}
+          docker run ${{ env.DOCKER_ARGS }} ${{ env.RASA_IMAGE }} train ${{ env.TRAIN_TYPE }} ${{ env.DEFAULT_ARGS }} ${{ env.FIXED_MODEL_ARGS }} ${{ env.FINE_TUNE }} ${{ inputs.train_args }}
         else
           echo "::warning::rasa train is disabled. To turn on the rasa train set the rasa_train parameter to 'true'."
         fi
@@ -302,6 +311,15 @@ runs:
             OUTPUT="${OUTPUT}\n$(python3 ${{ github.action_path }}/scripts/cross_validation_results.py)"
           fi
 
+          if [[ -f "${{ inputs.workspace }}/${{ inputs.result_directory }}/failed_test_stories.yml" ]]; then
+            TEST_FAILED=$(grep 'None of the test stories failed' README.md > /dev/null; echo $?)
+            if [[ $TEST_FAILED -eq 0 ]]; then
+              OUTPUT="${OUTPUT}\n```yml\n$(cat ${{ inputs.workspace }}/${{ inputs.result_directory }}/failed_test_stories.yml)```"
+            else
+              OUTPUT="${OUTPUT}\n\n#$(cat ${{ inputs.workspace }}/${{ inputs.result_directory }}/failed_test_stories.yml)"
+            fi
+          fi
+
           OUTPUT="${OUTPUT//$'\n'/'\n'}"
 
           curl -X POST -s -H "Authorization: token ${{ inputs.github_token }}" -H "Accept: application/vnd.github.v3+json"  \
diff --git a/scripts/cross_validation_results.py b/scripts/cross_validation_results.py
index a2d713b..1f8eb40 100644
--- a/scripts/cross_validation_results.py
+++ b/scripts/cross_validation_results.py
@@ -51,6 +51,7 @@ def entity_table():
     cols = ["support", "f1-score", "precision", "recall"]
     writer.headers = ["entity"] + cols
 
+    data.pop("accuracy", None)
     classes = list(data.keys())
     classes.sort(key=lambda x: data[x]["support"], reverse=True)